Would you rather own one asset or an empire?

In 1977, 20th Century Fox released a strange science-fiction movie that would soon become the highest-grossing film ever made.

The studio took a gamble that other movie production companies had rejected. Fox had backed the right director, financed the right movie, and introduced the world to a franchise that would ultimately generate billions of dollars.

Fox had helped produce a historic success.

But George Lucas had made the better bet.

While negotiating the details of the movie’s production, Lucas reportedly surrendered hundreds of thousands of dollars in his customary directing fees in exchange for something Fox considered far less valuable: control over the sequels and merchandising rights.

Fox owned a successful movie.

Lucas owned a franchise empire.

Credit: TracyHornbrook

Both sides recognized enough potential in Star Wars to move forward. The difference was how they structured their exposure to its success.

Investors rarely think about their portfolios in those terms. It’s not just the stocks you own, but how much.

It’s Not Just About Stock Picking

I’m probably like the rest of our Digest readers in that I spend a ton of time consuming financial media. I routinely get information from television, radio, podcasts, social media, and newspapers.

Nearly all of this coverage focuses on stock picking.

And that makes sense because most individual investors spend their time trying to find the best stocks to buy. They don’t spend any time thinking about how much of each stock to own to maximize their portfolio’s gains.

It’s easy to see why this can create pitfalls in your wealth-building strategy.

Imagine that you identify a small tech company that goes on to rise 500%.

Congratulations! That sounds like a life-changing investment.

But if you put only 1% of your portfolio into it, even with that extraordinary winner, the stock would add only approximately 5% to your total portfolio.

Now, imagine that you invested 20% of your money in another company and it fell by 50%. That single mistake costs your portfolio 10%.

You found a 500% winner – and yet you still ended up behind!

That’s not to say that stock picking is easy. There’s a reason why we depend so much on experts such as Louis Navellier, Luke Lango, and Eric Fry.

But these problems have become more acute in the age of AI. The market moves faster than ever and has produced some extraordinary winners.

Regular Digest readers will recognize some of these big winners that Louis, Luke, and Eric recommended to their subscribers.

Louis’ open Nvidia (NVDA) recommendation, for example, was recently showing a gain of approximately 5,000%.

That is enough to turn a $10,000 investment into roughly $500,000.

Luke Lango has four open recommendations up more than 1,000%, and several more above 500%.

He recommended Rocket Lab (RKLB) before it became a 10-bagger for one of his subscribers. According to that reader, he considered selling after the stock doubled. Instead, he decided to hold on and saw the stock rise approximately tenfold.

And Eric Fry recently took partial profits in Westgold Resources (WGXRF), with a gain of roughly 1,700%. Eric has more than 40 recommendations in his track record that went on to gain 10X.

These are extraordinary stock picks.

These kinds of gains can transform your financial life – if you own enough of the stocks producing them.

A 10-bagger may produce little more than a pleasant surprise if it represents only a tiny fraction of your portfolio.

And if you invest too heavily, even a promising company can expose you to painful losses when something goes wrong.

That’s why professional investors devote so much attention to portfolio construction.

They don’t merely ask: “Which stocks do we want to own?”

They also ask: “How much should we invest in each one?”                                                                                                                                       

Making the Decision Easier

And that brings me to an important announcement from legendary investor and Senior Quantitative Analyst Louis Navellier.

After nearly five decades of identifying some of the market’s most successful stocks, Louis has concluded that investors need more than another recommendation.

AI is moving too quickly. The potential rewards are becoming too large. And the divide between the companies benefiting from this revolution and those left behind is widening.

That is why Louis is preparing to make one of the most important announcements of his career.

On Aug. 19, he will join Luke and Eric for a special presentation about what they believe is coming next in the AI boom and a major change they are making to help investors navigate it.

They will also address the crucial question most investment research leaves unanswered:

Once you identify an extraordinary opportunity, how much should you own?

I’ve already had an opportunity to see what they will reveal, and it goes well beyond another AI prediction or individual stock recommendation.

It represents a fundamental change in how they can help investors pursue the tremendous opportunities ahead – all while addressing the risk that one wrong decision could overwhelm everything else they get right.

20th Century Fox helped create one of the most valuable entertainment franchises in history.

But George Lucas structured his stake so that the success of Star Wars could transform his life.

In the Age of AI, finding the right opportunity is only the beginning.

You must also make the right bet.

Click here to reserve your place for Louis’ important announcement with Luke and Eric.

And then circle your calendar for Aug. 19 at 10 a.m. ET.

It won’t just be about stock picks, but how to ensure you own the right amount.

Enjoy your weekend,

Luis Hernandez

Editor in Chief, InvestorPlace

The post The Painful Mistake After Finding a 10-Bagger appeared first on InvestorPlace.

Except Boeing just did. On purpose. And if you understand why, you understand where the next wave of AI money is headed.

On Monday, the Boeing-Archer deal was announced. Boeing (BA) handed three of its subsidiaries — Wisk Aero, SkyGrid, and Insitu — to Archer Aviation (ACHR). Three businesses. Two decades of investment. One of them generating over $200 million a year in defense revenue across 35 countries, with drones flown by the U.S. Navy.

The price? Zero dollars.

Boeing took stock instead. A 19.75% stake in Archer, plus options to buy more over the next four years — all laid out in a regulatory filing, not a marketing deck.

The market heard it. ACHR stock ripped 20% by mid-morning.

So why would Boeing do this? Simple. I spent 28 years on trading floors in Chicago, and I watched this exact trade a hundred times: when a market maker holds a position he can’t run properly, he doesn’t dump it at the bid — he swaps it to the guy who can run it and keeps a piece of the upside. That’s what Boeing did. CEO Kelly Ortberg has been shedding everything that isn’t commercial planes, defense, or space since he took over — he sold the Jeppesen flight-planning unit for $10.55 billion last year. But this time, instead of taking cash and walking away, Boeing kept a nearly 20% seat at the table and licensed back Wisk’s autonomy tech for its own future aircraft. Sell the headache, keep the upside. That’s not desperation. That’s a pro’s trade.

But here’s the part most investors will miss: the deal announcement gave Wall Street something more valuable than a stock pop.

It gave Wall Street new language.

“Physical AI” Just Entered the Chat

Archer didn’t call this a drone acquisition. It didn’t call it an eVTOL consolidation.

It called it an “end-to-end physical AI platform for aerospace and defense.”

Physical AI. Remember that phrase. You’re going to hear it a thousand times over the next year.

Here’s the plain-English version. The first wave of AI lived in a data center. It wrote your emails. It answered your questions. It made Nvidia the most valuable company in history.

Physical AI is what happens when that intelligence gets a body. Aircraft that fly themselves. Drones that navigate without a pilot. Air traffic systems that manage thousands of autonomous vehicles at once.

That’s what Archer just bought:

• Wisk Aero — six generations of autonomous electric aircraft, more than 1,700 test flights
• SkyGrid — the air traffic management software that keeps autonomous aircraft from hitting each other
• Insitu — military drones flown worldwide, including by the U.S. Navy, with 3,500+ systems built and $200M+ in annual revenue

Feed all of it — nearly two million combined flight hours of data — into Archer’s AI foundation model, called ZEE. That’s the platform.

Whether Archer executes on that vision is a different question. But the theme just got a name, a poster child, and a Boeing endorsement. Themes with all three don’t stay quiet.

The Tape Told You Everything at 10 A.M.

I don’t care what a press release says. I care what the money does.

So here’s what the money did on Monday.

ACHR jumped 20% — fine, that’s the deal stock, it’s supposed to move. Part of that pop was mechanical anyway: nearly 15% of Archer’s float was sold short, and shorts covering into a takeover headline is rocket fuel that has nothing to do with conviction.

The real tell was everything around ACHR:

• AeroVironment (AVAV) — up 9%
• Kratos Defense (KTOS) — up nearly 6%
• Red Cat Holdings (RCAT) — up 6%
• Planet Labs (PL) — up 5%

None of those companies were in the deal. Not one.

That’s called a sympathy move, and it’s one of the most honest signals in markets. Nobody issued a press release telling AVAV to rally 9%. Real buyers showed up because the deal re-priced what an autonomous-systems business is worth. Insitu — a drone maker doing $200 million a year — just got valued inside a “physical AI” wrapper, and every fund manager holding a comparable business did the same math before lunch.

Meanwhile Boeing itself? Up less than 1%. The market shrugged at the seller and chased the theme.

That’s what the tape can’t hide, folks. The money went straight to the drone complex.

Follow the Money: 3 Ways to Play Physical AI Stocks

I’m not going to hand you a “buy this now” list. What I’ll do is show you where the money is pointing, so you can do your own work.

The pure comp: AeroVironment (AVAV). If you want to know what Insitu is, look at AVAV. Military drones, loitering munitions, U.S. defense contracts. It led Monday’s sympathy rally for a reason — it’s the closest public company to the business Boeing just handed Archer. When the theme gets a re-rating, the cleanest comp gets it first.

The autonomy arms dealer: Kratos (KTOS). Kratos builds tactical drones and the autonomy software that flies them. If “physical AI” becomes the label funds put on their defense-tech sleeve, Kratos sits in the middle of it.

The small-cap torque: Red Cat (RCAT). Higher risk, higher beta. Red Cat’s Teal drones won a U.S. Army short-range reconnaissance program, and the stock moves violently when the drone theme catches a bid. This is the name that goes up the most when the theme is hot — and down the most when it isn’t. Size accordingly.

And a word on the obvious one everybody will mention: Palantir (PLTR) is the software layer of battlefield AI, but it’s already priced like everyone knows it. The fresh money in a new theme usually flows to the names that haven’t been discovered yet.

Read the Fine Print Before Chasing the Boeing-Archer Deal

Two things to keep in your back pocket before you chase anything.

The deal isn’t done. It’s expected to close by the end of 2026, pending antitrust review. Between now and then, Archer is a story stock with a $200 million revenue business attached to a press release, not a balance sheet.

Archer paid in paper. This was an all-stock deal. Archer just issued roughly 20% of itself to Boeing. Dilution is real, and existing shareholders paid for these assets whether they realize it or not.

None of that kills the theme. It just means the theme and the ticker are two different trades. You can believe in physical AI without believing ACHR at any price.

Physical AI Stocks: The Bottom Line on the New Theme

Twenty-eight years of watching order flow taught me one thing above everything else: nothing matters until the money moves.

On Monday, the money moved. Boeing swapped $200 million of annual revenue for equity in a startup. The drone complex re-rated in hours on a deal it wasn’t even part of. And Wall Street got handed a brand-new theme with a Fortune 50 company’s signature on it.

Chatbots were the first act. Physical AI — machines that fly, see, and decide — is the sequel.

The smart money already bought its ticket. The question is whether you’re watching the screen or the popcorn line.

P.S. After decades on the trading floor, here’s the most important lesson I’ve learned…

You don’t have to predict which way a stock will move to profit from earnings. You just have to know when the market is mispricing the move.

That’s the foundation of my Earnings Advantage strategy. We compare a stock’s historical earnings moves against the move options traders are pricing in today. When the market is underestimating the potential move, we buy both sides with defined risk — and let the stock tell us which side wins.

It’s the same system we’ve used to close over 70 trades at a 64% win rate in just two and a half years. That’s the edge I want to help everyone reading this gain. If you’re interested in finding out more about my system, just click here to see what Earnings Advantage has to offer.

The post Boeing-Archer Deal: Why Give Away a $200 Million Business — on Purpose? appeared first on InvestorPlace.

My colleague Luke Lango believes simply owning more AI stocks isn’t the answer. With opportunities emerging across chips, networking, energy, software and more, choosing the right mix is becoming increasingly important.

That’s why Luke, Eric Fry and I recently narrowed more than 200 recommendations down to roughly 20 stocks we believe stand out today.

We’ll unveil those picks and our recommended allocations in our AI Revolution Portfolio webinar on Wednesday, August 19, at 10 a.m. Eastern. You can sign up here to join us.

In today’s guest essay, Luke explains why building the right AI portfolio may matter more than ever.

Here’s Luke with the full story… 

****************

There was a time, just a few years ago, when AI investing felt easy.

You could buy Nvidia (NVDA), the hyperscalers, or the companies wiring up the world’s data centers. And then… you could basically stop thinking. The AI boom did the rest.

That simple playbook worked spectacularly.

But it’s no longer the right approach.

Meta (META) just released an open-weight AI model capable of running on an ordinary laptop. Google Maps can now order food, hunt for hotels, and carry out errands on your behalf. Microsoft (MSFT) is reportedly preparing another generation of custom AI chips. And Nvidia is organizing some of the world’s top AI labs around a shared family of open models.

Four developments in four different parts of the AI economy.

Together, they show how many new ways there are to invest in the AI boom.

Gone are the days when AI investing was centered on one chipmaker, one cloud platform, or one kind of technology. The boom is spreading – into personal devices, consumer agents, custom silicon, open-model ecosystems, networking, memory, power, and the software connecting all of it.

That is excellent news for long-term investors.

It also creates a problem.

An investor can understand every one of these trends, pick several good stocks, and still build a bad portfolio.

Finding winners is no longer the hardest part.

Figuring out how they fit together is.

One AI Boom, Several Different Trades

Glimmer Brings More AI Onto the PC

Start with Meta.

This week, the company released Muse Glimmer, a compact open-weight model designed to handle coding, administrative work, and other agentic tasks while running on a standard laptop or PC. Mark Zuckerberg paired the launch with a sweeping vision for “personal superintelligence,” where individuals can run powerful AI systems without depending entirely on a handful of centralized providers.

That pushes the AI trade onto the device.

If capable models can run continuously on consumer hardware, demand spreads beyond giant cloud clusters. AI PCs need better processors, more memory, larger storage systems, stronger connectivity, and efficient power management. The model may run locally, but an entire hardware stack has to support it.

Google Maps Moves From Navigation to Action

Then there is Google Maps.

What began as a navigation product evolved into a local-search engine. Now Google is turning it into something closer to a consumer agent.

Its latest Ask Maps features can help users order food, search for hotels that match specific preferences, find local events, and personalize results using information from other Google services.

Maps is beginning to steer the transaction itself, pulling cloud inference, payments, local-commerce software, restaurant technology, digital advertising, and the businesses inside Google’s distribution network into the trade.

Microsoft Wants More Control of the Chip Stack

Microsoft’s reported Maia 300 plans point to another corner of the market.

According to recent reporting, Microsoft could unveil its next-generation AI accelerator as early as September. The company has already spent years developing proprietary silicon to reduce costs, gain more control over its infrastructure, and lessen its dependence on outside chip suppliers.

Maia changes more than Microsoft’s chip bill.

A custom chip needs an architect. It needs a foundry. It needs advanced packaging, high-bandwidth memory, networking, power systems, cooling equipment, and racks capable of turning silicon into usable compute.

A hyperscaler designing its own accelerator does not remove the supply chain. It rearranges who gets paid.

Nvidia Is Building More Than Hardware

And Nvidia is pushing into yet another layer.

The company formed the Nemotron Coalition with Mistral AI, Cursor, LangChain, Perplexity, Black Forest Labs, and several other leading AI developers. The group is building open frontier models trained on Nvidia’s DGX Cloud, with the first shared foundation supporting the upcoming Nemotron 4 family.

Nvidia is still selling the picks and shovels.

Now it is helping organize the miners, too.

Its hardware dominance gives Nvidia a natural position at the center of an open-model ecosystem. More developers building on Nemotron means more workloads trained and served on Nvidia infrastructure.

AI Is Becoming Its Own Economy

Meta’s Glimmer is an edge-AI story.

Google Maps is a consumer-agent story.

Microsoft’s Maia program is a custom-silicon story.

Nemotron is a model-platform and developer-infrastructure story.

All four belong to the AI boom.

They do not belong in a portfolio for the same reason.

Same Boom, Different Economics

AI now has model makers, consumer platforms, chip designers, memory suppliers, network builders, power providers, and software companies helping agents carry out work.

Each group makes money differently. Each depends on different customers. And each carries a different set of risks.

A new open model may pressure premium API pricing while boosting demand for consumer GPUs. A custom chip can take share from Nvidia inside one cloud platform while creating new revenue for a foundry, an HBM supplier, and a networking company. A consumer agent can strengthen Google’s ecosystem while generating more work for payments and local-commerce providers.

That complexity comes with maturity. Capital is moving beyond the obvious names and into companies solving increasingly specific problems.

Our own results show what that can look like.

Lumentum (LITE), an optical-networking supplier that most investors once viewed as a niche component maker, is currently sitting on a roughly 645% gain from our August 2025 recommendation. Louis Navellier’s Nvidia position is up roughly 375%.

Those profits came from different layers of the same broad buildout: one from the chips doing the work, the other from the optical infrastructure moving the data.

The winners are multiplying across the AI economy.

A Collection of Good Stocks Is Not Necessarily a Good Portfolio

This is the point where AI investing gets harder.

Suppose an investor owns Microsoft, Amazon (AMZN), Alphabet (GOOGL), Nvidia, Broadcom (AVGO), Marvell (MRVL), Taiwan Semiconductor (TSM), Micron (MU), and several networking suppliers.

That may look diversified. In reality, much of the portfolio could depend on the same underlying variable: hyperscaler infrastructure spending.

If that spending ever slows, several positions may react at once.

The opposite problem can happen, too. An investor may own one exciting robotics stock, one experimental power company, and one small AI-software name. The themes are different, but the risk may be heavily concentrated in early-stage businesses with little room for execution mistakes.

Position size matters just as much as stock selection.

A profitable hyperscaler with hundreds of billions in contracted revenue should not carry the same weight as a speculative component supplier. A mature semiconductor leader should not be treated like an emerging agent platform. Two stocks operating in different industries may still depend on the same customer or capital-spending cycle.

A good AI portfolio gives every holding a job.

Some positions form the core. Others provide exposure to emerging layers of the market. Smaller allocations create room for higher-upside ideas without allowing one failed thesis to overwhelm the entire portfolio.

The goal is coherence.

That has become much harder as the number of credible AI investments has grown.

Our Success Created a New Problem

InvestorPlace’s AI research team has produced more than 200 recommendations over the past year.

That reflects the scale of the opportunity. It also leaves readers with one glaring question: What are they supposed to do with all of them?

Owning 200 stocks is not a strategy. Neither is chasing whichever recommendation happens to be newest.

Investors need to know which ideas deserve a place in the portfolio, which ones overlap, and how much capital each position should receive. That is the problem our newly rebuilt AI Revolution Portfolio is designed to solve.

The last time we did this, the portfolio more than doubled the Nasdaq’s return.

Following its December 2024 rebalance through July 23, the AI Revolution Portfolio gained 58%. Over that same stretch, the Nasdaq rose 25%, the S&P 500 gained 24.4%, and the Dow advanced 19%.

The lesson from that outperformance goes beyond any single winner. Our portfolio captured gains across multiple parts of the AI economy while organizing those positions around one coherent market view.

Rebuilding the AI Revolution Portfolio

Since that last rebalance, the market has changed again.

Models are moving onto personal computers. Agents are beginning to transact. Hyperscalers are designing their own chips. Nvidia is helping build an open-model ecosystem. New infrastructure bottlenecks are appearing as quickly as old ones get solved.

So we went back to work.

Louis Navellier, Eric Fry, and I have gone through our AI research and narrowed that sprawling universe into roughly 20 stocks we collectively believe deserve capital now.

The market is creating winners across models, agents, chips, optics, memory, energy, and infrastructure. No single recommendation can capture all of it. And simply adding more tickers does not solve the problem.

AI is creating more winners than investors can track.

Now the real edge comes from knowing which ones deserve your money, how they complement one another, and how large each position should be.

That’s why next Wednesday, August 19, at 10 a.m. Eastern, we’ll be holding a special event to reveal a brand-new tool that can help investors properly allocate their AI portfolios.

Plus, Louis will be making a huge announcement about a new role he’ll be taking on.

Click here to reserve your spot for the special event now.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post Which AI Stocks Actually Belong in Your Portfolio? appeared first on InvestorPlace.

The optical-networking company just reported roughly $1.01 billion in quarterly revenue, more than double what it generated a year ago. Adjusted earnings jumped to $3.23 per share, and management guided the current quarter to between $1.225 billion and $1.275 billion in revenue. Wall Street had expected less on both counts.

The underlying AI thesis is working.

Data centers are growing larger. AI clusters are connecting more chips. More data has to move between those chips at greater speeds. And copper wiring can only carry that traffic so far before power consumption and physical constraints become a problem.

That is where Lumentum comes in.

Its lasers and optical components help move data through AI infrastructure using light. As the buildout scales, that technology becomes more essential.

Nvidia (NVDA) clearly agrees. In March, it invested $2 billion in Lumentum and made a multibillion-dollar purchase commitment for advanced laser components. Lumentum is also expanding U.S. manufacturing to support the next generation of AI data centers.

Last August, I recommended Lumentum in the AI Revolution Portfolio, where Louis Navellier, Eric Fry, and I bring together our highest-conviction AI ideas.

That position is now up roughly 680%.

The business continues to execute, AI optics demand keeps strengthening, and the original investment case remains firmly intact. 

But Lumentum’s success points to a larger lesson.

A stock can keep getting better while the account around it becomes more dependent on it.

That is the hidden cost of winning in AI.

Why Lumentum Stock Became an AI Optical Networking Winner

Lumentum was hardly an obvious AI winner when we recommended it.

The stock did not have Nvidia’s brand recognition. It did not own a hyperscale cloud platform. And it was not building a frontier AI model.

But AI data centers were running into a problem.

The chips were getting faster, and the compute clusters were getting larger. Yet all those processors still had to communicate with one another.

That made networking increasingly important.

An AI cluster can contain thousands of high-end chips working on the same model. If data cannot move freely, and at speed, between those chips, it wastes expensive computing resources. More chips alone do not solve that problem. What must improve is the connections between them.

Lumentum fits that bill to a tee.

That was the opportunity we saw way back in August 2025. Since then, each earnings report has made the connection harder to ignore.

The market eventually caught on that optics had become a critical piece of AI infrastructure, and Lumentum’s stock surged.

The company earned it. Now consider what a return like that can do to a portfolio…

How a 680% Winner Changes Portfolio Concentration

Suppose Lumentum started as 5% of a portfolio. After a 680% gain, with every other holding unchanged, it would now account for roughly 29% of the entire portfolio.

A position that started at 3% would now account for more than 19%.

The investor did nothing wrong. In fact, they were spectacularly right.

But the portfolio has changed.

A measured position now drives nearly a third of the account. One earnings report, customer delay, supply-chain problem, or change in AI infrastructure spending can now have an outsized impact.

None of this makes Lumentum a sell. We still like the business very much.

But “hold” should never mean “stop thinking.”

After a major run, investors need to reassess the stock’s role in the broader account: how much performance now depends on it, which other holdings share its risks, and whether the overall mix still reflects the original plan. 

Position size is part of the investment thesis, not an administrative detail worked in after the fact.

Once a winner controls a substantial share of an account, the next dollar should not automatically follow the last one.

New capital may do more by strengthening another part of the portfolio. That allows investors to build around the winner without abandoning the thesis that produced it.

“We like this stock” tells an investor what looks attractive – but not how much to own, whether to keep adding, or where the next dollar belongs.

Stock selection finds the opportunity. Allocation determines the role it plays.

Every New AI Stock Competes for the Same Portfolio Dollar

The AI market keeps producing fresh opportunities, but capital is finite. Every new position has to earn its place beside the winners already in a portfolio and the risks already being carried.

As valuations shift, new opportunities emerge, and modest positions grow into major ones, the ideal mix changes, too.

That broader evolution led Louis Navellier, Eric Fry, and me to revisit our AI Revolution Portfolio.

After combing through more than 200 AI recommendations, Louis, Eric, and I narrowed the field to roughly 20 stocks we believe deserve capital now.

We also assigned a recommended allocation to every holding. Subscribers will see which companies made the cut, how we believe the holdings should fit together, and how much of the portfolio we think each idea deserves.

The AI boom is still creating exceptional opportunities.

Lumentum shows the power of one great pick. Building a complete strategy takes another layer of work: deciding which opportunities belong together and how much capital each one deserves.

That is what Louis, Eric, and I – together, with all our decades of combined experience – have built.

On Wednesday, August 19, we’re unveiling the rebuilt AI Revolution Portfolio.

Sign up now to see it as soon as it goes live.

The post Lumentum’s 680% Run Created a New Portfolio Problem appeared first on InvestorPlace.

Today, we’re wrapping things up with Wall Street icon Louis Navellier, who dives into the tightrope the Federal Reserve is walking, trying to keep inflation under control while supporting the labor market. He explains what the recent CPI and PPI numbers mean for investors and highlights where the best opportunities currently exist.

Louis explores these opportunities in greater detail during an upcoming special presentation with InvestorPlace Senior Analysts Eric Fry and Luke Lango. Click here for details on that.

Now, we’ll let Louis take it from here.

On August 7, 1974, a 24-year-old French high-wire artist named Philippe Petit was preparing to do something no one had ever done before.

Shortly after 7 a.m., Petit stepped onto the roof of the South Tower of the World Trade Center. Dressed in all black and carrying only a long balancing pole, he made his way onto a steel cable stretched between the Twin Towers – 1,350 feet above the streets of New York.

Source: twintowers_nyc / Instagram

For nearly an hour, he walked back and forth between the towers. He bowed to the crowd below, sat on the wire, and, at one point, even lay down on it.

He did it all without a harness or safety net. And it remains one of the most remarkable high-wire feats in history.

Now, more than 50 years later, the Federal Reserve is trying to pull off a balancing act of its own.

Of course, the stakes are very different. But the Fed has its own tightrope to walk.

You see, the Fed has two mandates: keeping inflation under control and supporting the labor market. And right now, those two sides are giving Fed officials a lot to think about.

We got a reminder of that last Friday, when the July jobs report showed that the U.S. economy lost 23,000 jobs. On top of that, May and June payroll growth was revised lower by a combined 103,000 jobs.

Clearly, the labor market is starting to lose some momentum.

Now, there is a lot of confusion about the job market, because the unemployment rate actually fell from 4.2% to 4.1%.

Somehow, a million people disappeared from the workforce. So, whether that’s baby boomers retiring or some workers being deported, I honestly have no idea.

But I do know that the Fed has an unemployment mandate. And if we’re losing jobs, the Fed won’t want to raise rates.

Then this week, we got fresh inflation data, with the Consumer Price Index (CPI) report yesterday and the Producer Price Index (PPI) report today.

So today, let’s take a closer look at the latest inflation numbers, what they mean for the Fed and the stock market – and where I believe some of the biggest opportunities are taking shape right now.

A Closer Look at Inflation

Yesterday’s CPI report came in largely in line with economists’ expectations.

Consumer prices rose just 0.1% in July, dropping the annual inflation rate to 3.4% from 3.5% in June. Core inflation, which excludes the more volatile food and energy categories, rose 0.2% for the month and slowed to 2.5% year over year.

So, overall, inflation continues to move in the right direction.

And the best news came from shelter costs.

Shelter accounts for a significant share of the CPI, so when those costs are running hot, they can have a big impact on the overall inflation number.

Well, shelter costs rose just 0.1% in July, matching June’s increase. That tells me one of the biggest sources of inflation pressure is finally cooling off. And that’s very good news.

Energy prices also fell 1.5% in July, thanks in large part to a 2.9% drop in gasoline prices. That was certainly welcome news. Still, energy prices remain 14.7% higher than they were a year ago.

So, energy is still one area I’m watching closely. We all know tensions in the Middle East continue to create uncertainty around oil prices. But I have consistently said that the Fed cannot control energy costs, and it would be foolish to hike rates just because energy prices are high.

Of course, the CPI only tells us what consumers are paying. To get a fuller picture of inflation, we also need to look at what businesses are paying further up the supply chain.

And that’s where today’s PPI report comes in. And the news there was even better.

Producer prices were unchanged in July, better than the 0.2% increase economists expected. Year-over-year, producer prices rose 4.7%, down from 5.5% in June.

It was an outstanding report. And the details were encouraging, too.

Goods prices fell 0.7% for the month, while food prices declined 0.9% and energy prices dropped 3.1%. Services prices rose just 0.2%.

So, when you put the CPI and PPI together, I think the takeaway is pretty clear: Inflation has cooled off dramatically.

And that takes a lot of pressure off the Fed.

What This Means for the Fed

And that brings us back to the Fed’s balancing act.

As we’ve seen over the past week, inflation is cooling while the labor market is losing some momentum.

The only real concern in today’s PPI report was that some of the components that feed into the Fed’s preferred PCE inflation gauge could move higher. And that has some people worried the Fed may still have to raise rates in September.

There’s also been a lot of attention on the fact that the federal funds rate (3.50% to 3.75%) is still above the two-year Treasury yield. That’s led some investors to argue that either market rates have to move lower or the Fed will eventually have to raise its own rate.

But market rates are already moving lower. Today, we are seeing the two-year yield at about 4.14% – that’s down from a recent high of 4.36% about three weeks ago.

So, with inflation cooling this dramatically, I don’t think the Fed needs to do anything.

To me, it looks pretty good for no Fed rate hike.

That’s a pretty encouraging setup for the stock market.

Where I’m Focusing My Attention Now…

So, what’s next for the markets? Let me walk you through what I’m seeing.

The S&P 500’s earnings will likely be up by about 50% by the time earnings season is over.

The acceleration in earnings is just unreal – and I’m seeing strength in a lot of different groups.

And that’s just the S&P. Many of my fundamentally superior stocks are posting earnings growth in excess of 100%!

That’s why I remain so bullish on this market.

And one area where I continue to see some of the biggest opportunities is artificial intelligence.

As the AI buildout continues, companies are spending enormous sums on data centers, chips, power and other infrastructure. And that spending is creating opportunities across a wide range of industries.

But there’s another side to that story.

The bigger this AI boom gets, the more potential investments there are to keep track of.

I, along with my InvestorPlace colleagues Luke Lango and Eric Fry, have all spent years searching for the best ways to profit from this trend.

And we’ve uncovered a ton of opportunities along the way.

At a certain point, though, simply finding another good stock isn’t necessarily the hardest part.

The harder question is… Which opportunities deserve a place in your portfolio? How much should you put into each one? And how should all those investments fit together?

Those are questions I’ve been thinking about a lot lately.

And Luke, Eric and I have been working behind the scenes on what I believe is a much better way to answer them.

Now, I don’t want to get ahead of myself today.

But next Wednesday, August 19, the three of us are making a major announcement that could change the way you approach the AI opportunity from here.

You see, I’m shifting my focus because I think there’s an even better way I can help you take advantage of the opportunities in this market.

To help make sense of all these opportunities… narrow the field… and give you a clearer way to put your money to work in what I believe remains one of the greatest wealth-building trends of our lifetime.

I’ll explain exactly what we mean during our special event next Wednesday, August 19.

I hope you’ll join me on to hear the full story.

You can reserve your spot right here. 

Sincerely,

Louis Navellier

Editor, Market 360

The post Cooling Inflation Opens the Door for This Trade appeared first on InvestorPlace.

If you need proof, look no further than the SEC filings of Space Exploration Technologies Corp. (SPCX).

According to those documents, part of Musk’s restricted stock award is tied to what the company officially calls the “Mars Colony Milestone.”

We’re not talking about planting a flag on Mars or sending a handful of astronauts there one day.

SpaceX defines the milestone as establishing a permanent human colony on Mars with at least one million people. Musk’s award is also tied to a series of market-value targets that eventually climb as high as $6 trillion.

Folks, when a company is literally putting a million-person colony on Mars into its executive compensation plan, you can understand why investors get excited.

SpaceX has one of the greatest stories on Wall Street. This is Elon Musk’s rocket company – the business behind Starlink, reusable rockets and some of the most ambitious plans in the history of private spaceflight.

But a great story and a great stock are two very different things.

Back on June 12, I warned Market 360 readers about the hype surrounding SpaceX.

There had been a lot of fuss around the company’s initial public offering (IPO) back in mid-June. And it wasn’t hard to understand why.

Investors rushed in, and SPCX surged about 40% in its first two days of trading.

But as I warned my followers, all that excitement didn’t automatically make SpaceX a sound investment.

I also warned that SpaceX’s unusually small public float could eventually put pressure on shares as restrictions on insider stock began to expire. That process started last week.

Since then, shareholders have gotten a crash course in the difference between a great story and a great stock. SPCX fell sharply from its post-IPO highs, dropping about 45% at one point, before rebounding again.

The stock is now roughly flat since it went public.

And this week, the company finally gave us something much more useful to evaluate than hype: its first earnings report.

So, in today’s Market 360, let’s take a closer look at what SpaceX actually reported and why its enormous AI spending has Wall Street nervous. Then I’ll share what this tells us about the increasingly difficult decisions investors face in today’s AI boom.

SpaceX Is Growing – But at an Enormous Cost

SpaceX reported second-quarter revenue of $7.8 billion, up about 92% year-over-year and ahead of analysts’ estimates of $6.8 billion.

That is serious growth, folks.

Starlink is generating recurring revenue. Falcon rockets continue launching satellites. And customers across aviation, maritime, telecommunications and defense are spending heavily on SpaceX’s services.

So, let me be clear: SpaceX is becoming a real commercial business. And a 92% increase in sales is exactly the kind of growth that gets my attention.

But sales growth is only one part of the equation. The company still posted a net loss of $541 million, or $0.09 per share, due largely to its enormous spending on AI and infrastructure.

SpaceX spent nearly $16 billion on AI infrastructure during the quarter, pushing its total capex to roughly $18.4 billion.

Think about that for a moment. SpaceX generated $7.8 billion in quarterly revenue. Yet it spent more than twice that amount during the same three months.

That doesn’t automatically make SpaceX a bad company or even a bad investment. Plenty of great businesses have gone through periods of enormous spending before generating huge profits.

But it does put the burden of proof on the company.

The question is not whether SpaceX can attract customers or grow sales. It clearly can.

The question is whether all that spending will eventually generate enough earnings and cash flow to justify the price investors are being asked to pay for the stock.

That matters especially because all of this is happening during one of the best earnings environments of my lifetime.

Our friends at FactSet report that the S&P 500 is currently on track to achieve 47.4% year-over-year earnings growth in the second quarter.

By the time NVIDIA Corporation (NVDA) and Micron Technology Inc. (MU) announce their earnings, it will likely be over 50%. 

Folks, that is extraordinary. And this is why it’s vital we focus on fundamentally superior stocks.

Wall Street is willing to reward growth. But investors increasingly want to see that growth translate into stronger earnings and a clear path toward future profits.

That distinction is especially important in artificial intelligence.

AI Is Becoming a Capital-Allocation Story

Companies are spending staggering sums on chips, data centers, power, networking and other AI infrastructure. Goldman Sachs estimates that $1 trillion will be spent globally in 2026 alone.

But spending billions of dollars on AI doesn’t guarantee billions of dollars in profits.

Ultimately, the biggest winners will be the companies that can take those enormous investments and turn them into durable sales, earnings and cash flow.

And we’re already seeing evidence of that this earnings season.

Microsoft Corporation (MSFT) just reported 43% growth in Azure revenue, while its operating income climbed 18%. Alphabet Inc.’s (GOOG) Google Cloud revenue surged 82%, while Cloud operating income more than tripled to $8.8 billion. And Amazon.com Inc.’s (AMZN) Amazon Web Services grew 37%, with operating income jumping 64%.

These companies are spending enormous sums on AI, too. The difference is that they’re already showing investors where the payoff is coming from.

In other words, AI is becoming a capital-allocation story. And that principle applies to investors, too.

For decades, I’ve used quantitative analysis to help separate strong stocks from weak ones. That’s why I built the systems that eventually became Stock Grader (subscription required).

I wanted a disciplined way to cut through Wall Street’s noise and focus on companies with superior sales growth, earnings growth, earnings momentum and institutional buying pressure.

I’ll continue doing exactly that. But the AI boom has created another challenge.

Ever since OpenAI released ChatGPT to the public on November 30, 2022, my InvestorPlace colleagues and I have spent years digging into opportunities for investors to profit.

We’re talking about semiconductors, software, data centers, power generation, networking, cooling systems and plenty of other businesses that most investors never would have considered “AI stocks” a few years ago.

We’ve found some tremendous winners along the way.

But that success has also created a problem.

Over the past year alone, my colleagues and I have collectively issued more than 200 recommendations across our research.

Obviously, no individual investor should own more than 200 stocks simply because we happened to recommend them.

At some point, finding more ideas stops making your financial life easier. It starts making it harder.

I want to change that.

Finding a Great Stock Is Only the First Decision

And that’s where stock selection gives way to portfolio construction.

Suppose Stock Grader helps you identify 10 fundamentally superior stocks. Or 20. Which ones deserve the most money? Which should play smaller roles? And how do you make sure those individually strong stocks actually fit together?

Those are different questions from simply asking whether a stock is a “buy.”

Think back to SpaceX for a moment. The company just reported 92% sales growth. That’s impressive.

Does that make SPCX a buy? Not for me – at least not yet. As I’ve said before, I want a full year of trading data before Stock Grader weighs in.

But identifying whether SpaceX eventually deserves a “buy” is only the first decision. If it does, how much should you own compared with every other fundamentally superior opportunity available to you?

The point is that the AI boom has given us a pretty nice problem, folks.

We no longer have to worry about good ideas. We have to worry about capital allocation.

So after 47 years in this business, I’ve decided I need to make a change…

A Major Change Is Coming on August 19

Back in 2023, I sat down with my InvestorPlace colleagues Luke Lango and Eric Fry to begin working on a project that grew directly out of the problem I just described.

Simply put, we’ve gone through InvestorPlace’s large universe of AI recommendations and selected what we consider our absolute best ideas.

The result was a portfolio of stocks that we considered the crème de la crème.

I’m proud to say that the portfolio has delivered a return of roughly 106%.

And since we last rebalanced it in December 2024, through July 23 this year, our picks have gained 58%. Meanwhile, the S&P 500 gained 24.4%, and the NASDAQ rose 25%.

After speaking to Luke and Eric, we all agreed it was high time for another rebalance.

The result? A newly rebuilt portfolio of roughly 20 stocks. And it all goes live on Wednesday, August 19.

But that’s not all. Next Wednesday, I will announce the biggest change to my role at InvestorPlace in decades.

And before anyone gets the wrong idea, I’m not going anywhere, and I’m certainly not giving up Stock Grader.

What is changing is the way I intend to approach the problem I’ve just described.

For most of my career, I’ve focused on helping readers find fundamentally superior stocks. But what’s become clear to me in the midst of this AI boom is that finding great picks is only part of the job.

While I can’t give you individual advice, my goal is to help investors better allocate all of these amazing picks into a portfolio that makes sense and delivers stellar risk-adjusted returns.

I’ll explain exactly what I mean on August 19. I hope you’ll join us.

You can go here to sign up for free now.

Sincerely,

Louis Navellier

Editor, Market 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

Alphabet Inc. (GOOG), Micron Technology Inc. (MU) and NVIDIA Corporation (NVDA)

The post Why SpaceX Is a Lesson in Hype Vs. Fundamentals – and What to Do Now appeared first on InvestorPlace.

He had not… yet.

Like most analysts and advisors tracking SpaceX, the IPO was blowing through every valuation and screener condition imaginable. So, the client asked if they could just buy 10 shares anyway.

The advisor did as asked, later likening the trade to buying a lottery ticket after the jackpot already hit a billion dollars. The odds are not in your favor, but you buy anyway for the buzz and the hope.

But the space trade is much, much bigger than any single stock.

Space stocks spent the six weeks after the SpaceX IPO in a brutal drawdown. The sector ran hot into the listing, then was crushed once the hype passed. But now we’re staring down the barrel of a major turnaround, and I want to walk you through why this setup is one of my favorite trades in the market currently.

In short, we’re seeing long-term winners that have worked through short-term corrections, which have flipped into short-term rebounds. When that happens in a sector this early in its growth curve, you want to be positioned before the move, not after it.

There are two reasons for the turnaround in space stocks. First, the entire space basket reported earnings, and the reports were good almost across the board. Second, SpaceX cleared its first major post-IPO share lockup without triggering the wave of insider selling that bears (me included) worried about. Both were clearing events. And both point toward a sector that’s ready to surge.

Here are five stocks I recommend buying on this rebound:

5 Space Stocks to Buy Now

Redwire Corporation (RDW) is a space infrastructure company built through a mix of internal engineering and an aggressive M&A strategy: eleven acquisitions to date, most recently Edge Autonomy. The result is a business split across two segments. Space covers next-generation spacecraft, large space infrastructure such as solar arrays and power systems, and microgravity manufacturing. Defense Tech covers combat-proven unmanned aircraft systems (the Stalker and Penguin platforms) and sensor and payload systems (Octopus ISR). Redwire is less a single-product company than a rollup of critical, often single-source components and capabilities that other space and defense programs depend on. The numbers back up the story. In the second quarter, Redwire delivered record revenue of $117.1 million, up 89.6% year over year, with record gross margins of 27.8%. Backlog hit a record $542.1 million, up 64.5% year over year (the fifth consecutive quarter of backlog growth) on a book-to-bill ratio of 1.42. Management reaffirmed full-year revenue guidance of $450 million to $500 million, roughly 42% growth at the midpoint, and the company ended the quarter with $557.8 million in cash after a $487.9 million capital raise. That gives Redwire real firepower to keep pursuing accretive M&A and to fund expansion projects like the new Microgravity Center of Excellence in Georgetown, Indiana, and a 164,000-square-foot Defense Tech production expansion in Huntsville, Alabama.

BlackSky Technology Inc. (BKSY) operates a constellation of high-resolution imaging satellites paired with real-time analytics through its Spectra software platform. Its core intelligence and AI subscription business hit a $100 million annualized revenue run rate in the second quarter, up 50% sequentially. Management says that revenue level unlocks real operating leverage, meaning incremental subscription dollars now drop to the bottom line at a far higher rate. Adjusted EBITDA turned solidly positive at roughly $5 million, a 14.2% margin and a $7.5 million improvement from a year earlier. BlackSky raised $150 million in fresh capital during the quarter and now holds liquidity north of $300 million. The chart shows the stock reclaiming its 200-day and 50-day moving averages with a bullish MACD crossover. I expect a new high above the prior peak of $51.63, potentially reaching $60 to $70 in the coming weeks to months.

Rocket Lab USA, Inc. (RKLB) is following the same playbook SpaceX wrote: evolving from a rocket launch company into a vertically integrated space and AI business through its pending Iridium Communications acquisition, its push into spectrum, and talk of orbital data centers. Second-quarter revenue reached $234 million, up 62% year over year and above estimates, with a backlog of $2.36 billion and more than $1 billion in new contracts signed across the quarter and the week after. The adjusted loss came in at $8.8 million, far better than management’s guided range of $20 million to $26 million. Rocket Lab lost its 200-day moving average in mid-July for the first time since 2024, but it has since reclaimed that level, and I want to see $78 hold as support. If it does, this stock could put in its biggest rebound yet, potentially reaching $200 from around $150 to $160.

AST SpaceMobile, Inc. (ASTS) is building a satellite network that connects directly to ordinary, unmodified smartphones, a real technological edge over Starlink’s hardware-dependent approach. Verizon, AT&T, Vodafone and 21 of Europe’s top 25 carriers have expressed interest in the technology. Backlog grew to $1.3 billion, and the company landed more than $100 million in new U.S. government contracts tied to national security priorities, including the Golden Dome missile defense initiative. A new $1.15 billion convertible note priced at the company’s lowest-ever coupon, near 1.6%, pushed pro forma cash to nearly $4 billion. The chart lags the rest of the group because it has not reclaimed its 200-day moving average, but the bounce off the roughly $53 low looks legitimate, with a bullish MACD crossover pushing above the zero line. I recommend buying the rebound here even without full technical confirmation.

Space Exploration Technologies Corp. (SPCX) is the head of the snake for this entire trade. Second-quarter revenue hit $7.8 billion, up 92% year over year, and EBITDA reached $3.5 billion, up 191%. All three segments grew: Space up 29%, connectivity up 66%, and the AI segment up 247%. That AI unit turned EBITDA-positive for the first time, at $1.1 billion. Management guided toward more than $100 billion in annualized revenue by December, backed by roughly $100 billion in cash following the IPO and a $25 billion bond offering. When the SpaceX rally cooled after the IPO, this entire sector fell with it. Now that SpaceX is rebounding, the rest of the group is rebounding, too. You cannot separate the two stories.

The Bottom Line on Space Stocks

One name notably absent from this list is Planet Labs (PL). I recommend the stock long-term, but it still trades below its 200-day moving average and its earnings report remains roughly a month out. Four of the five stocks above have earnings confirmation, and all five show technical confirmation. Planet Labs has neither yet.

The lottery-ticket logic from that SpaceX buyer applies to this whole sector. You are not betting the farm here. You are making a calibrated bet on businesses with growing backlogs, improving margins, and balance sheets now flush with fresh capital, at exactly the moment their charts are turning higher.

That is the setup, and I think space stocks are ready to rocket over the next few weeks to months.

The post 5 Space Stocks Ready to Rocket Higher After the SpaceX Hangover appeared first on InvestorPlace.

On Monday, we heard from Brian Hunt of Money & Megatrends. On Tuesday and Wednesday, our macro investing expert Eric Fry of The Speculator took over.

Today, we turn to Luke Lango, InvestorPlace’s lead technology analyst, who will explain how the AI trade now spans multiple layers – including chips, cloud platforms, agents, memory, networking, power, and software – and is no longer a single dominant trade. Emphasizing diversification, he’ll also describe what it takes to build a strong portfolio.

Additionally, he’ll share how that’s shaped upcoming developments for AI Revolution Portfolio, the service he manages alongside senior analysts Eric Fry and Louis Navellier. You can learn more about that here.

Take it away, Luke.

There was a time, just a few years ago, when AI investing felt easy.

You could buy Nvidia (NVDA), the hyperscalers, or the companies wiring up the world’s data centers. And then… you could basically stop thinking. The AI boom did the rest.

That simple playbook worked spectacularly.

But it’s no longer the right approach.

Meta (META) just released an open-weight AI model capable of running on an ordinary laptop. Google Maps can now order food, hunt for hotels, and carry out errands on your behalf. Microsoft (MSFT) is reportedly preparing another generation of custom AI chips. And Nvidia is organizing some of the world’s top AI labs around a shared family of open models.

Four developments in four different parts of the AI economy.

Together, they show how many new ways there are to invest in the AI boom.

Gone are the days when AI investing was centered on one chipmaker, one cloud platform, or one kind of technology. The boom is spreading – into personal devices, consumer agents, custom silicon, open-model ecosystems, networking, memory, power, and the software connecting all of it.

That is excellent news for long-term investors.

It also creates a problem.

An investor can understand every one of these trends, pick several good stocks, and still build a bad portfolio.

Finding winners is no longer the hardest part.

Figuring out how they fit together is.

One AI Boom, Several Different Trades

Glimmer Brings More AI Onto the PC

Start with Meta.

This week, the company released Muse Glimmer, a compact open-weight model designed to handle coding, administrative work, and other agentic tasks while running on a standard laptop or PC. Mark Zuckerberg paired the launch with a sweeping vision for “personal superintelligence,” where individuals can run powerful AI systems without depending entirely on a handful of centralized providers.

That pushes the AI trade onto the device.

If capable models can run continuously on consumer hardware, demand spreads beyond giant cloud clusters. AI PCs need better processors, more memory, larger storage systems, stronger connectivity, and efficient power management. The model may run locally, but an entire hardware stack has to support it.

Google Maps Moves From Navigation to Action

Then there is Google Maps.

What began as a navigation product evolved into a local-search engine. Now Google is turning it into something closer to a consumer agent.

Its latest Ask Maps features can help users order food, search for hotels that match specific preferences, find local events, and personalize results using information from other Google services. 

Maps is beginning to steer the transaction itself, pulling cloud inference, payments, local-commerce software, restaurant technology, digital advertising, and the businesses inside Google’s distribution network into the trade. 

Microsoft Wants More Control of the Chip Stack

Microsoft’s reported Maia 300 plans point to another corner of the market.

According to recent reporting, Microsoft could unveil its next-generation AI accelerator as early as September. The company has already spent years developing proprietary silicon to reduce costs, gain more control over its infrastructure, and lessen its dependence on outside chip suppliers.

Maia changes more than Microsoft’s chip bill.

A custom chip needs an architect. It needs a foundry. It needs advanced packaging, high-bandwidth memory, networking, power systems, cooling equipment, and racks capable of turning silicon into usable compute.

A hyperscaler designing its own accelerator does not remove the supply chain. It rearranges who gets paid.

Nvidia Is Building More Than Hardware

And Nvidia is pushing into yet another layer.

The company formed the Nemotron Coalition with Mistral AI, Cursor, LangChain, Perplexity, Black Forest Labs, and several other leading AI developers. The group is building open frontier models trained on Nvidia’s DGX Cloud, with the first shared foundation supporting the upcoming Nemotron 4 family.

Nvidia is still selling the picks and shovels.

Now it is helping organize the miners, too.

Its hardware dominance gives Nvidia a natural position at the center of an open-model ecosystem. More developers building on Nemotron means more workloads trained and served on Nvidia infrastructure.

AI Is Becoming Its Own Economy

Meta’s Glimmer is an edge-AI story.

Google Maps is a consumer-agent story.

Microsoft’s Maia program is a custom-silicon story.

Nemotron is a model-platform and developer-infrastructure story.

All four belong to the AI boom.

They do not belong in a portfolio for the same reason.

Same Boom, Different Economics

AI now has model makers, consumer platforms, chip designers, memory suppliers, network builders, power providers, and software companies helping agents carry out work.

Each group makes money differently. Each depends on different customers. And each carries a different set of risks.

A new open model may pressure premium API pricing while boosting demand for consumer GPUs. A custom chip can take share from Nvidia inside one cloud platform while creating new revenue for a foundry, an HBM supplier, and a networking company. A consumer agent can strengthen Google’s ecosystem while generating more work for payments and local-commerce providers.

That complexity comes with maturity. Capital is moving beyond the obvious names and into companies solving increasingly specific problems.

Our own results show what that can look like.

Lumentum (LITE), an optical-networking supplier that most investors once viewed as a niche component maker, is currently sitting on a roughly 645% gain from our August 2025 recommendation. Louis Navellier’s Nvidia position is up roughly 375%. 

Those profits came from different layers of the same broad buildout: one from the chips doing the work, the other from the optical infrastructure moving the data.

The winners are multiplying across the AI economy.

A Collection of Good Stocks Is Not Necessarily a Good Portfolio

This is the point where AI investing gets harder.

Suppose an investor owns Microsoft, Amazon (AMZN), Alphabet (GOOGL), Nvidia, Broadcom (AVGO), Marvell (MRVL), Taiwan Semiconductor (TSM), Micron (MU), and several networking suppliers.

That may look diversified. In reality, much of the portfolio could depend on the same underlying variable: hyperscaler infrastructure spending.

If that spending ever slows, several positions may react at once.

The opposite problem can happen, too. An investor may own one exciting robotics stock, one experimental power company, and one small AI-software name. The themes are different, but the risk may be heavily concentrated in early-stage businesses with little room for execution mistakes.

Position size matters just as much as stock selection.

A profitable hyperscaler with hundreds of billions in contracted revenue should not carry the same weight as a speculative component supplier. A mature semiconductor leader should not be treated like an emerging agent platform. Two stocks operating in different industries may still depend on the same customer or capital-spending cycle.

A good AI portfolio gives every holding a job.

Some positions form the core. Others provide exposure to emerging layers of the market. Smaller allocations create room for higher-upside ideas without allowing one failed thesis to overwhelm the entire portfolio.

The goal is coherence.

That has become much harder as the number of credible AI investments has grown.

Our Success Created a New Problem

InvestorPlace’s AI research team has produced more than 200 recommendations over the past year.

That reflects the scale of the opportunity. It also leaves readers with one glaring question: What are they supposed to do with all of them?

Owning 200 stocks is not a strategy. Neither is chasing whichever recommendation happens to be newest.

Investors need to know which ideas deserve a place in the portfolio, which ones overlap, and how much capital each position should receive. That is the problem our newly rebuilt AI Revolution Portfolio is designed to solve.

The last time we did this, the portfolio more than doubled the Nasdaq’s return.

Following its December 2024 rebalance through July 23, the AI Revolution Portfolio gained 58%. Over that same stretch, the Nasdaq rose 25%, the S&P 500 gained 24.4%, and the Dow advanced 19%.

The lesson from that outperformance goes beyond any single winner. Our portfolio captured gains across multiple parts of the AI economy while organizing those positions around one coherent market view.

Rebuilding the AI Revolution Portfolio

Since that last rebalance, the market has changed again.

Models are moving onto personal computers. Agents are beginning to transact. Hyperscalers are designing their own chips. Nvidia is helping build an open-model ecosystem. New infrastructure bottlenecks are appearing as quickly as old ones get solved.

So we went back to work.

Louis Navellier, Eric Fry, and I have gone through our AI research and narrowed that sprawling universe into roughly 20 stocks we collectively believe deserve capital now.

The market is creating winners across models, agents, chips, optics, memory, energy, and infrastructure. No single recommendation can capture all of it. And simply adding more tickers does not solve the problem.

AI is creating more winners than investors can track.

Now the real edge comes from knowing which ones deserve your money, how they complement one another, and how large each position should be.

Louis, Eric, and I are about to unveil the newly rebuilt AI Revolution Portfolio.

Sign up to see the portfolio, the recommended allocations, and the thinking behind every position right here.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post How to Build an AI Portfolio That Actually Holds Up appeared first on InvestorPlace.

Shortly after 7 a.m., Petit stepped onto the roof of the South Tower of the World Trade Center. Dressed in all black and carrying only a long balancing pole, he made his way onto a steel cable stretched between the Twin Towers – 1,350 feet above the streets of New York.

Source: twintowers_nyc / Instagram

For nearly an hour, he walked back and forth between the towers. He bowed to the crowd below, sat on the wire, and, at one point, even lay down on it.

He did it all without a harness or safety net. And it remains one of the most remarkable high-wire feats in history.

Now, more than 50 years later, the Federal Reserve is trying to pull off a balancing act of its own.

Of course, the stakes are very different. But the Fed has its own tightrope to walk.

You see, the Fed has two mandates: keeping inflation under control and supporting the labor market. And right now, those two sides are giving Fed officials a lot to think about.

We got a reminder of that last Friday, when the July jobs report showed that the U.S. economy lost 23,000 jobs. On top of that, May and June payroll growth was revised lower by a combined 103,000 jobs.

Clearly, the labor market is starting to lose some momentum.

Now, there is a lot of confusion about the job market, because the unemployment rate actually fell from 4.2% to 4.1%.

Somehow, a million people disappeared from the workforce. So, whether that’s baby boomers retiring or some workers being deported, I honestly have no idea.

But I do know that the Fed has an unemployment mandate. And if we’re losing jobs, the Fed won’t want to raise rates.

Then this week, we got fresh inflation data, with the Consumer Price Index (CPI) report yesterday and the Producer Price Index (PPI) report today.

So, in today’s Market 360, let’s take a closer look at the latest inflation numbers, what they mean for the Fed and the stock market – and where I believe some of the biggest opportunities are taking shape right now.

A Closer Look at Inflation

Yesterday’s CPI report came in largely in line with economists’ expectations.

Consumer prices rose just 0.1% in July, dropping the annual inflation rate to 3.4% from 3.5% in June. Core inflation, which excludes the more volatile food and energy categories, rose 0.2% for the month and slowed to 2.5% year over year.

So, overall, inflation continues to move in the right direction.

And the best news came from shelter costs.

Shelter accounts for a significant share of the CPI, so when those costs are running hot, they can have a big impact on the overall inflation number.

Well, shelter costs rose just 0.1% in July, matching June’s increase. That tells me one of the biggest sources of inflation pressure is finally cooling off. And that’s very good news.

Energy prices also fell 1.5% in July, thanks in large part to a 2.9% drop in gasoline prices. That was certainly welcome news. Still, energy prices remain 14.7% higher than they were a year ago.

So, energy is still one area I’m watching closely. We all know tensions in the Middle East continue to create uncertainty around oil prices. But I have consistently said that the Fed cannot control energy costs, and it would be foolish to hike rates just because energy prices are high.

Of course, the CPI only tells us what consumers are paying. To get a fuller picture of inflation, we also need to look at what businesses are paying further up the supply chain.

And that’s where today’s PPI report comes in. And the news there was even better.

Producer prices were unchanged in July, better than the 0.2% increase economists expected. Year-over-year, producer prices rose 4.7%, down from 5.5% in June.

It was an outstanding report. And the details were encouraging, too.

Goods prices fell 0.7% for the month, while food prices declined 0.9% and energy prices dropped 3.1%. Services prices rose just 0.2%.

So, when you put the CPI and PPI together, I think the takeaway is pretty clear: Inflation has cooled off dramatically.

And that takes a lot of pressure off the Fed.

What This Means for the Fed

And that brings us back to the Fed’s balancing act.

As we’ve seen over the past week, inflation is cooling while the labor market is losing some momentum.

The only real concern in today’s PPI report was that some of the components that feed into the Fed’s preferred PCE inflation gauge could move higher. And that has some people worried the Fed may still have to raise rates in September.

There’s also been a lot of attention on the fact that the federal funds rate (3.50% to 3.75%) is still above the two-year Treasury yield. That’s led some investors to argue that either market rates have to move lower or the Fed will eventually have to raise its own rate.

But market rates are already moving lower. Today, we are seeing the two-year yield at about 4.14% – that’s down from a recent high of 4.36% about three weeks ago.

So, with inflation cooling this dramatically, I don’t think the Fed needs to do anything.

To me, it looks pretty good for no Fed rate hike.

That’s a pretty encouraging setup for the stock market.

Where I’m Focusing My Attention Now…

So, what’s next for the markets? Let me walk you through what I’m seeing.

The S&P 500’s earnings will likely be up by about 50% by the time earnings season is over.

The acceleration in earnings is just unreal – and I’m seeing strength in a lot of different groups.

And that’s just the S&P. Many of my fundamentally superior stocks are posting earnings growth in excess of 100%!

That’s why I remain so bullish on this market.

And one area where I continue to see some of the biggest opportunities is artificial intelligence.

As the AI buildout continues, companies are spending enormous sums on data centers, chips, power and other infrastructure. And that spending is creating opportunities across a wide range of industries.

But there’s another side to that story.

The bigger this AI boom gets, the more potential investments there are to keep track of.

I, along with my InvestorPlace colleagues Luke Lango and Eric Fry, have all spent years searching for the best ways to profit from this trend.

And we’ve uncovered a ton of opportunities along the way.

At a certain point, though, simply finding another good stock isn’t necessarily the hardest part.

The harder question is… Which opportunities deserve a place in your portfolio? How much should you put into each one? And how should all those investments fit together?

Those are questions I’ve been thinking about a lot lately.

And Luke, Eric and I have been working behind the scenes on what I believe is a much better way to answer them.

Now, I don’t want to get ahead of myself today.

But next Wednesday, August 19, the three of us are making a major announcement that could change the way you approach the AI opportunity from here.

You see, I’m shifting my focus because I think there’s an even better way I can help you take advantage of the opportunities in this market.

To help make sense of all these opportunities… narrow the field… and give you a clearer way to put your money to work in what I believe remains one of the greatest wealth-building trends of our lifetime.

I’ll explain exactly what we mean during our special event next Wednesday, August 19.

I hope you’ll join me on to hear the full story.

You can reserve your spot right here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Why The Fed’s Balancing Act Is Tilting in Wall Street’s Favor appeared first on InvestorPlace.

Tom Yeung here with today’s Smart Money.

Last year, over 315,000 Americans were injured in distracted driving accidents.

If a driver takes their eyes off the road for just five seconds to send a text, they would have driven the length of an entire football field at 55mph by the time they looked back up. At 75mph, they would have traveled two full city blocks.

Taking your eyes off the road can have serious consequences. The same is true for investing.

Markets have offered no shortage of distracting events lately. War in the Middle East… earnings announcements… oil prices… cybersecurity breaches…

Each of these stories is worth watching. But keep your head turned too long, and you risk missing out on an even bigger shift happening right in front of you.

The biggest shift right now is artificial intelligence, possibly the most consequential technology of our lifetimes.

Consultancy IDC estimates that AI will add $22.3 trillion cumulatively to the global economy through 2030, five times more than what India generates per year. And if anything, I suspect that figure will prove conservative. After all, the world’s workers collectively earn roughly $50 trillion in wages every year. If AI continues to improve at its current pace, it will soon compete for the single largest pool of money on Earth.

In other words, while investors are busy reacting to the latest headline, AI is quietly reshaping one of the biggest forces “driving” the economy: work itself.

So today, let’s keep our eyes on the road and follow the winding AI opportunity – from the jobs it will transform to the companies supplying the tools that will power what comes next.

The Future of Work

What would a world without tutors look like? Or accountants? Or even CEOs?

It’s a fair question because each of these jobs is already getting squeezed by AI.

Tutoring companies like Chegg Inc. (CHGG) and Nerdy Inc. (NRDY) have seen their share prices plummet since the launch of ChatGPT in 2022. Over 80% of high school students report using AI for help with schoolwork, and almost 95% do at the college level.

Accountants face a double squeeze. The pipeline of new accounting graduates is shrinking, and AI bookkeeping software is only getting better. That’s causing business owners to offload busywork to AI accounting programs with buzzy names like “Digits,” “Xero,” and “Puzzle.”

Even the corner office isn’t safe. In 2022, Hong Kong-listed gaming firm NetDragon Websoft appointed an AI-powered virtual CEO named Tang Yu to run its flagship subsidiary. The company’s shares went on to outperform the Hang Seng index in the months that followed. Tang Yu, it should be noted, did not require a corporate jet.

“Fine,” says the skeptic. “White-collar work goes digital. But AI can’t rewire a house. Learn a trade!”

For now, that’s true. But I’d encourage the skeptics to spend five minutes watching videos of Unitree’s humanoid robots dancing, boxing, and doing backflips. The Chinese firm shipped 5,500 of these machines last year and is targeting annual production rates of 190,000 units.

And here’s the thing: these robots can learn new tricks.

Unitree itself already offers an app store called “UniStore” where users can download new skills for their robot. And the store is designed to support a whole range of future abilities, including camera tracking, grasp detection, and other job-related skills.

That means it’s only a matter of time before every blue-collar job could face its own “ChatGPT moment” as new skills are added to a robotic app store.

Now, none of this is a doomsday forecast. In 1900, about 40% of Americans worked on farms; today, less than 2% do. Technological displacement is a very old story, and it has always created enormous wealth.

 However, the 20th century barely paid the people picking the crops. It paid the people who owned the tractors.

So, if robots become the new machines doing the work, the biggest opportunities may lie with the companies supplying the “tractors” of the AI Revolution.

Buying the AI Revolution

A logical question to then ask is: How does one buy a tractor dealership in 2026?

The obvious answer is to try investing in the robot and AI developers themselves. But the problem is that most of them aren’t for sale.

OpenAI and Anthropic are private companies. And the AI startups that do go public often charge sky-high prices for their shares… if you’re lucky enough to land any at all. Unitree said on Monday that its $900 million Shanghai initial public offering was more than 8,000 times oversubscribed. That means the average investor requesting 8,000 shares would only receive 1.

For now, ordinary investors are locked out of the showroom.

Fortunately, there are still ways to invest in the AI Revolution without getting burned.

Consider Advanced Micro Devices Inc. (AMD), a company Eric recommended in 2025. The chip designer had long existed in the shadow of Intel Corp. (INTC) and almost went bankrupt in the mid-2010s before current CEO Lisa Su took over.

Then came the turnaround. The struggling AMD soon inked deals with PlayStation and Xbox to sell gaming chips, and then poured the cash into designing a new type of chip called “Zen.”

Zen architecture turned out to be fantastic. It was modular, relatively easy to manufacture and fast – exactly the qualities AI datacenters needed.

That meant investors did not have to pay high prices to buy up companies like OpenAI… or even Nvidia Corp. (NVDA), which was already a $420 billion company when ChatGPT was launched in late 2022. Instead, they could snap up a turnaround chipmaker at a massive discount and own the company making the “tractor engines” of the AI Revolution.

The Next Stage of the AI Revolution

Of course, AMD’s value has now been discovered. The company is worth almost $800 billion, and Eric sold the stock later that year for a quick triple-digit gain.

But the AI Revolution will provide plenty more triple-digit opportunities in places you least expect.

I’m talking about the rare earth magnets needed in every robotic joint…

Every custom chip used in a “hyperscale” AI datacenter…

Every new solar panel that powers these devices…

And that’s why Eric spent months working with InvestorPlace Senior Analysts Louis Navellier and Luke Lango to identify the companies positioned to power this next stage.

And next Wednesday, August 19, at 10 a.m. Eastern, they’ll be holding a special event to discuss why they expect the AI Revolution to continue. They’ll also reveal their brand-new tool that can help investors properly allocate their AI portfolios.

Plus, Louis will be making a huge announcement about a new role he’ll be taking on.

Click here to reserve your spot for the special event now.

 Until next time,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

The post Don’t Get Distracted from the $22 Trillion AI Opportunity Ahead appeared first on InvestorPlace.

You could buy Nvidia (NVDA), the hyperscalers, or the companies wiring up the world’s data centers. And then… you could basically stop thinking. The AI boom did the rest.

That simple playbook worked spectacularly.

But it’s no longer the right approach.

Meta (META) just released an open-weight AI model capable of running on an ordinary laptop. Google Maps can now order food, hunt for hotels, and carry out errands on your behalf. Microsoft (MSFT) is reportedly preparing another generation of custom AI chips. And Nvidia is organizing some of the world’s top AI labs around a shared family of open models.

Four developments in four different parts of the AI economy.

Together, they show how many new ways there are to invest in the AI boom.

Gone are the days when AI investing was centered on one chipmaker, one cloud platform, or one kind of technology. The boom is spreading – into personal devices, consumer agents, custom silicon, open-model ecosystems, networking, memory, power, and the software connecting all of it.

That is excellent news for long-term investors.

It also creates a problem.

An investor can understand every one of these trends, pick several good stocks, and still build a bad portfolio.

Finding winners is no longer the hardest part.

Figuring out how they fit together is.

One AI Boom, Several Different Trades

Glimmer Brings More AI Onto the PC

Start with Meta.

This week, the company released Muse Glimmer, a compact open-weight model designed to handle coding, administrative work, and other agentic tasks while running on a standard laptop or PC. Mark Zuckerberg paired the launch with a sweeping vision for “personal superintelligence,” where individuals can run powerful AI systems without depending entirely on a handful of centralized providers.

That pushes the AI trade onto the device.

If capable models can run continuously on consumer hardware, demand spreads beyond giant cloud clusters. AI PCs need better processors, more memory, larger storage systems, stronger connectivity, and efficient power management. The model may run locally, but an entire hardware stack has to support it.

Google Maps Moves From Navigation to Action

Then there is Google Maps.

What began as a navigation product evolved into a local-search engine. Now Google is turning it into something closer to a consumer agent.

Its latest Ask Maps features can help users order food, search for hotels that match specific preferences, find local events, and personalize results using information from other Google services. 

Maps is beginning to steer the transaction itself, pulling cloud inference, payments, local-commerce software, restaurant technology, digital advertising, and the businesses inside Google’s distribution network into the trade. 

Microsoft Wants More Control of the Chip Stack

Microsoft’s reported Maia 300 plans point to another corner of the market.

According to recent reporting, Microsoft could unveil its next-generation AI accelerator as early as September. The company has already spent years developing proprietary silicon to reduce costs, gain more control over its infrastructure, and lessen its dependence on outside chip suppliers.

Maia changes more than Microsoft’s chip bill.

A custom chip needs an architect. It needs a foundry. It needs advanced packaging, high-bandwidth memory, networking, power systems, cooling equipment, and racks capable of turning silicon into usable compute.

A hyperscaler designing its own accelerator does not remove the supply chain. It rearranges who gets paid.

Nvidia Is Building More Than Hardware

And Nvidia is pushing into yet another layer.

The company formed the Nemotron Coalition with Mistral AI, Cursor, LangChain, Perplexity, Black Forest Labs, and several other leading AI developers. The group is building open frontier models trained on Nvidia’s DGX Cloud, with the first shared foundation supporting the upcoming Nemotron 4 family.

Nvidia is still selling the picks and shovels.

Now it is helping organize the miners, too.

Its hardware dominance gives Nvidia a natural position at the center of an open-model ecosystem. More developers building on Nemotron means more workloads trained and served on Nvidia infrastructure.

AI Is Becoming Its Own Economy

Meta’s Glimmer is an edge-AI story.

Google Maps is a consumer-agent story.

Microsoft’s Maia program is a custom-silicon story.

Nemotron is a model-platform and developer-infrastructure story.

All four belong to the AI boom.

They do not belong in a portfolio for the same reason.

Same Boom, Different Economics

AI now has model makers, consumer platforms, chip designers, memory suppliers, network builders, power providers, and software companies helping agents carry out work.

Each group makes money differently. Each depends on different customers. And each carries a different set of risks.

A new open model may pressure premium API pricing while boosting demand for consumer GPUs. A custom chip can take share from Nvidia inside one cloud platform while creating new revenue for a foundry, an HBM supplier, and a networking company. A consumer agent can strengthen Google’s ecosystem while generating more work for payments and local-commerce providers.

That complexity comes with maturity. Capital is moving beyond the obvious names and into companies solving increasingly specific problems.

Our own results show what that can look like.

Lumentum (LITE), an optical-networking supplier that most investors once viewed as a niche component maker, is currently sitting on a roughly 645% gain from our August 2025 recommendation. Louis Navellier’s Nvidia position is up roughly 375%. 

Those profits came from different layers of the same broad buildout: one from the chips doing the work, the other from the optical infrastructure moving the data.

The winners are multiplying across the AI economy.

A Collection of Good Stocks Is Not Necessarily a Good Portfolio

This is the point where AI investing gets harder.

Suppose an investor owns Microsoft, Amazon (AMZN), Alphabet (GOOGL), Nvidia, Broadcom (AVGO), Marvell (MRVL), Taiwan Semiconductor (TSM), Micron (MU), and several networking suppliers.

That may look diversified. In reality, much of the portfolio could depend on the same underlying variable: hyperscaler infrastructure spending.

If that spending ever slows, several positions may react at once.

The opposite problem can happen, too. An investor may own one exciting robotics stock, one experimental power company, and one small AI-software name. The themes are different, but the risk may be heavily concentrated in early-stage businesses with little room for execution mistakes.

Position size matters just as much as stock selection.

A profitable hyperscaler with hundreds of billions in contracted revenue should not carry the same weight as a speculative component supplier. A mature semiconductor leader should not be treated like an emerging agent platform. Two stocks operating in different industries may still depend on the same customer or capital-spending cycle.

A good AI portfolio gives every holding a job.

Some positions form the core. Others provide exposure to emerging layers of the market. Smaller allocations create room for higher-upside ideas without allowing one failed thesis to overwhelm the entire portfolio.

The goal is coherence.

That has become much harder as the number of credible AI investments has grown.

Our Success Created a New Problem

InvestorPlace’s AI research team has produced more than 200 recommendations over the past year.

That reflects the scale of the opportunity. It also leaves readers with one glaring question: What are they supposed to do with all of them?

Owning 200 stocks is not a strategy. Neither is chasing whichever recommendation happens to be newest.

Investors need to know which ideas deserve a place in the portfolio, which ones overlap, and how much capital each position should receive. That is the problem our newly rebuilt AI Revolution Portfolio is designed to solve.

The last time we did this, the portfolio more than doubled the Nasdaq’s return.

Following its December 2024 rebalance through July 23, the AI Revolution Portfolio gained 58%. Over that same stretch, the Nasdaq rose 25%, the S&P 500 gained 24.4%, and the Dow advanced 19%.

The lesson from that outperformance goes beyond any single winner. Our portfolio captured gains across multiple parts of the AI economy while organizing those positions around one coherent market view.

Rebuilding the AI Revolution Portfolio

Since that last rebalance, the market has changed again.

Models are moving onto personal computers. Agents are beginning to transact. Hyperscalers are designing their own chips. Nvidia is helping build an open-model ecosystem. New infrastructure bottlenecks are appearing as quickly as old ones get solved.

So we went back to work.

Louis Navellier, Eric Fry, and I have gone through our AI research and narrowed that sprawling universe into roughly 20 stocks we collectively believe deserve capital now.

The market is creating winners across models, agents, chips, optics, memory, energy, and infrastructure. No single recommendation can capture all of it. And simply adding more tickers does not solve the problem.

AI is creating more winners than investors can track.

Now the real edge comes from knowing which ones deserve your money, how they complement one another, and how large each position should be.

Louis, Eric, and I are about to unveil the newly rebuilt AI Revolution Portfolio.

Sign up to see the portfolio, the recommended allocations, and the thinking behind every position right here.

The post AI Is Creating More Winners Than Investors Can Track appeared first on InvestorPlace.

Today, we’re passing the baton to Thomas Yeung, Eric Fry’s research analyst and fellow Digest writer. After watching the spectacular rise – and equally spectacular collapse – of a high-profile AI hedge fund, Tom is eager to explain what individual investors can learn from it.

More importantly, he shows why Eric believes the next phase of the AI boom may reward a very different group of companies than the last one. If Tom’s essay leaves you wanting the bigger picture, go ahead and watch Eric’s free Market Shock presentation, where he explains his “Golden Rivets” framework and shares the companies he’s watching most closely.

We’ll let Tom take it from here…

Hello, Reader.

There is usually a “tuition cost” that comes with learning how to invest.

• That first stomach-churning loss…
• That first painful tax bill…
• That first accidental “buy” order instead of a “sell”…

Everyone remembers their early mistakes. It’s what makes you a better trader.

That’s because learning to invest by paper trading is like figuring out how to swim by reading a book. There is no substitute for diving in and trying not to drown.

Now, most of us pay that tuition a little at a time. Preferably very early on.

But one AI hedge fund appears to have paid a very expensive tuition bill in recent weeks.

I’m talking about Situational Awareness, an AI fund run by one of Wall Street’s brightest new stars, Leopold Aschenbrenner. The 24-year-old former OpenAI researcher first gained notice in 2024 after publishing a lengthy essay called “Situational Awareness: The Decade Ahead” that predicted the rise of artificial general intelligence (AGI).

Then Aschenbrenner put money behind that idea. He launched a hedge fund with the same name and built enormous positions around the AI boom.

For a while, the results looked almost supernatural. The fund gained 2,000% in 2025, and another 439% in the first half of 2026. Situational Awareness was worth $45 billion at its peak.

But then AI stocks hit a speed bump this summer.

Soon, the hedge fund began losing money. Then much more. So much, in fact, that it was forced to dump whatever it could. It ultimately sold its public-stock portfolio to a different hedge fund, Ken Griffin’s Citadel, notching an 80% loss.

In other words, Aschenbrenner had seen the AI future before almost everyone else…

But he had not built a portfolio that could survive the trip.

Fortunately, you don’t need a billion-dollar hedge fund – or a mountain of leverage – to profit from the AI Revolution.

Today, I’ll explain why simply being right about AI isn’t enough… lay out the two qualities I believe separate long-term winners from eventual blowups… and introduce you to one company I think fits that description.

Then, I’ll show you where you can find three more stocks Eric Fry is watching…

The Right Thesis, The Wrong Trade

In fairness, I believe Aschenbrenner remains directionally correct about AI.

AI systems are becoming more capable. Businesses are spending hundreds of billions of dollars to build data centers and build better AI models. The AI Revolution will have many years of growth ahead.

However, a correct prediction is not automatically a good investment.

Imagine someone knowing in 1997 that the internet would transform the global economy. They would have been absolutely right. And if they had put their life savings into Amazon.com Inc. (AMZN), they would have made millions… if not billions of dollars. The stock is up more than 300,000% since its listing in 1997.

But what if that same investor had bought Pets.com instead? After all, Pets.com was also an early e-commerce player. Besides, it had a sock-puppet mascot that showed up in a Super Bowl ad and on Good Morning America. Jeff Bezos never thought of doing that!

Instead, Pets.com turned out to be a total disaster. The pet food delivery company could not figure out how to become profitable, and the stock went from an IPO price of $11 down to $0.19 before it was totally liquidated in 2001. Hundreds of employees lost their jobs, and investors were wiped out.

The same will be true of the AI Revolution. Not every AI firm will succeed, and some will fail spectacularly.

But that’s not really what doomed Situational Awareness. The fund’s biggest problem wasn’t that it believed in AI. It was that it used enormous leverage to amplify those bets. When AI stocks stumbled, even temporarily, those leveraged positions quickly became impossible to maintain.

That’s an important lesson for individual investors. You can be absolutely right about the future… and still lose money if you own the wrong companies, pay too much for them, or take on too much risk.

The Right Way to Play the AI Revolution

You’re probably now wondering how to separate the “Amazon.com successes” from the “Pets.com flops” of the AI Revolution.

Here, I have some good news for you. In my experience, great businesses usually share a few common characteristics, even in industries moving as quickly as AI:

1. A wide business moat. Some AI companies own valuable technology and enjoy real pricing power. These are called “moats” because they protect those companies from competition. And they’re a key reason for a company’s long-term success.

2. The right price. The best investments are bought cheaply before everyone has discovered their worth. If a stock today is worth $1,000 per share, an investor would have made far greater profits if they had bought for $10… or $1… or better yet $0.10.

Those are two of the qualities my colleague Eric Fry looks for when researching AI investments.

Eric isn’t simply searching for “the next Nvidia” or “the next Amazon.” Even though there are some fantastic mega-cap AI companies out there, these stocks have already been discovered by just about every person on Earth with a working brokerage account.

In fact, if Amazon rose another 300,000% because of its AI business, it would be worth almost $9 quadrillion. If you spent $1 billion per day, it would take roughly 25,000 years to burn through that amount!

Nor is Eric trying to replicate the highly leveraged approach that helped Situational Awareness generate spectacular gains – and equally spectacular losses. Extraordinary returns are wonderful if you can keep them. But if your portfolio loses 80% every time the market hits a rough patch, you’re probably not going to stay in the game very long.

Instead, Eric focuses his search on a core group of companies that are building AI’s “Golden Rivets.” These are the specific, irreplaceable pieces needed to construct and power the AI buildout.

These Golden Rivet producers are not necessarily the companies receiving the loudest television coverage. Nor are they being bought up by the hottest AI hedge funds in town. In many cases, they are old-economy businesses that Wall Street overlooked while everyone chased chips and chatbots.

That is precisely what makes them interesting.

One example is Teradyne Inc. (TER). Rather than competing to build the next AI model, Teradyne supplies the sophisticated automated testing equipment and software that semiconductor manufacturers rely on to ensure increasingly complex AI chips actually work before they leave the factory.

Whether Nvidia Corp. (NVDA), Advanced Micro Devices Inc. (AMD), or another chipmaker wins the AI race, those chips still need to be tested. That’s exactly the kind of “Golden Rivets” business Eric likes to own.

These are the firms that will be fueling the big AI names. They will be building the chips… powering the data centers… and perhaps even running AI servers in space.

Teradyne is one of four semiconductor-related companies Eric discusses in his free Market Shock presentation. There, he explains why he believes AI’s next phase could reward these overlooked “Golden Rivets” businesses far more than today’s crowded AI trades—and reveals the other three stocks currently on his radar.

Every investor pays tuition eventually. The trick is paying a few hundred dollars… instead of a few billion. Hopefully, today’s lesson saves you from the latter.

If you’d like to see the rest of Eric’s “Golden Rivets” framework, I think you’ll get a great deal out of his free Market Shock presentation.

Regards,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

P.S. Eric believes the AI boom is entering a new phase. Instead of chasing the same crowded winners, he is studying the less-obvious businesses supplying the irreplaceable pieces the entire industry needs. In his free Market Shock presentation, he explains this “Golden Rivets” framework and shares more than a dozen stock tickers he is watching. See it here.

The post 4 AI Stocks We Think Can Survive the Shakeout appeared first on InvestorPlace.

Contrarian investing naturally draws a lot of heat for going “against” market trends, and sometimes for good reason. Simply being a contrarian without purpose is a losing strategy.

That is why, although some of my recommendations can seem “against” the grain, I consider myself an opportunistic investor.

Many of the most successful investment recommendations of my career came from stocks that Wall Street had written off or overlooked. They were down-and-outers that most investors were avoiding or ignoring.

For example, in June 2017, I recommended buying SolarEdge Technologies Inc. (SEDG) and selling The Kraft Heinz Co. (KHC). At the time, Wall Street was overwhelmingly bearish on SolarEdge and bullish on Kraft.

The results?

One year later, SolarEdge was up 139%, while Kraft was down 24%.

Four years later, SolarEdge had soared 1,282%, while Kraft was still down 42%.

And this is just one of many examples.

The lesson is simple: I’m not looking to go against the crowd just for the sake of being different. I’m looking for opportunities where the potential reward outweighs the risk – particularly when a catalyst could help turn an overlooked company or sector around.

That’s the same lens I’m applying to the AI boom today.

Artificial intelligence is perhaps the largest market trend in history. While many investors have made incredible profits from leading companies developing AI, such as Nvidia Corp. (NVDA) and Amazon.com Inc. (AMZN), the physical ingredients essential to building out this technology are becoming increasingly scarce.

And that’s exactly where I’m putting my attention: on the companies supplying the resources AI desperately needs.

In today’s Smart Money, I’ll show you why the raw materials behind the AI boom could be one of its most overlooked opportunities.

Then, like a nesting doll, I’ll reveal a hidden play within that overlooked theme – a turnaround opportunity hiding one layer deeper.

From the Obvious Trade to the Overlooked One

If power is the blood circulating through data center infrastructure, metals are the bones. In effect, every ton of metal pulled from the ground is a claim on the AI buildout.

This is important because AI’s explosive growth is creating a bottleneck in the raw materials needed to build it. Unlike software-as-a-service (SaaS) vendors or chip designers, metals companies don’t need to guess which AI model wins or which agent framework dominates; they just need to deliver the raw materials that make the entire ecosystem possible.

The “obvious” trade here has been copper, due to its vital role in data centers and power grids, both of which require large quantities of metal for electricity. For example, to sustain current growth, we need to mine as much copper in the next 18 years as in the past 10,000 years combined.

Copper itself reached record prices in late 2025, and has remained elevated in 2026. The Global X Copper Miners ETF (COPX), which tracks global companies involved in the exploration, mining, and refining of copper, is up almost 100% in the last year.

But there’s a less obvious trade to be made…

Aluminum demand is also accelerating.

Every high-voltage line that feeds an AI data hub consumes one to two tons of aluminum per megawatt delivered. Each new stretch of long-distance transmission deepens the world’s appetite for this versatile metal. From 104 million tons of demand in 2024 to an estimated 120 million by 2030, global aluminum consumption is set to grow almost as relentlessly as copper’s.

That’s the demand side of the equation. The supply side is where things get interesting.

Why the Smelters Are Restarting Now

Western aluminum production has become profitable enough to restart some idled smelters, the furnaces used to melt raw materials.

Two such smelters are set to come back from the dead: Magnitude 7 Metals’ New Madrid smelter in Missouri and Norsk Hydro ASA’s (NHY.OL) Slovalco smelter in Slovakia.

The facilities closed in 2024 and 2022, respectively, because aluminum prices were too low and electricity costs had become too high.

Now, the market has shifted from years of overcapacity to a much tighter supply environment, improving the economics of bringing some idled capacity back online. And creating an opportunity for these “zombie” smelters to come back to life.

New Madrid plans to start a 75,000-ton-per-year potline by the end of the year, with the possibility of further ramp-up in 2027. Slovalco, owned by both Hydro and Penta Investments Group, also plans to restart 75,000 tons of capacity, with the remaining 100,000 tons depending on external conditions after 2030.

But that’s not all. There is already proof in the aluminum pudding.

While New Madrid and Slovalco are preparing to restart aluminum production, the revival is already underway in South Carolina.

Last month, Century Aluminum’s Mt. Holly smelter in the Palmetto State announced that it has officially returned to full capacity. Aiming to produce about 50,000 more metric tons per year, Century Aluminum CEO Jess Gary said it will increase the country’s aluminum output by 10%, adding to the 30% the aluminum producer already accounts for.

Aluminum’s rising demand is evident in its price. The U.S. delivery premium has surged to roughly $2,450 per ton above the London Metal Exchange (LME) basis price. Meanwhile, the LME basis price is increasing, climbing from $2,200 per ton at the beginning of 2024 to $3,305 now.

Together, these developments point to a market undergoing a shift. Aluminum producers are bringing capacity back online, just as demand for the metal is accelerating.

This is exactly the kind of setup I look for: an industry where the fundamentals are improving, but where the market may not yet fully appreciate the opportunity.

And it brings me back to the investment philosophy I outlined earlier…

Where Contrarian Meets Opportunity

I am simply looking for a catalyst that could drive a recovery. And more often than not, the biggest catalysts aren’t found in the industries or companies that everyone’s already watching.

They’re found in what those companies desperately need.

Right now, that is raw materials. And within that overlooked theme, I believe aluminum offers an especially interesting opportunity.

But that metal is just one opportunity hiding in plain sight. Silver, platinum, palladium, aluminum, and lithium are all necessary physical components for the continued AI boom. And as demand for raw materials rises, so, too, could the opportunities for the companies supplying them.

That’s why,in my free Market Shock presentation, I name five stocks that I believe could benefit from rising demand for these critical materials.

They include:

• A major uranium producer powering the nuclear renaissance
• A global mining giant with major exposure to iron ore and other critical metals.
• A leading copper and zinc producer, with a growing portfolio of copper projects.
• A diversified miner producing manganese, nickel, lithium and mineral sands.
• A growing copper producer with operations in Brazil and additional exposure to gold.

These are companies tightly correlated with rising demand for raw materials.

That, ultimately, is what my approach is all about. Not simply going against the crowd, but identifying where the next opportunity could emerge before the rest of the market catches on.

Click here to learn the names of the companies for free.

Regards,

Eric Fry

The post How My “Against-the-Grain” Approach Finds AI’s Hidden Winners appeared first on InvestorPlace.

Today’s guest essay by macro-investing expert Eric Fry, editor of The Speculator, examines how the AI boom is entering a new phase. With physical supplies for AI now limited, Eric believes the businesses that will come out on top are the less-obvious suppliers of the irreplaceable pieces the entire industry needs. Below, he identifies two of the three main bottlenecks affecting AI and the kinds of companies that could become major winners.

For more on his investing framework and to discover more than a dozen stock tickers Eric is watching, watch his new free Market Shock presentation here.

Take it away, Eric.

Hello, Reader.

In a crossword puzzle, every answer connects. Solve one clue, and another piece suddenly falls into place.

Here’s one: Three words investors hate to see: “supply is ____”

Seven letters across. One answer.

Limited.

That word is becoming one of the most important clues in the AI investment puzzle.

The world wants more AI – more chips, more servers, more electricity, more data centers. But the supply of these critical resources is failing to keep up with demand.

And when supply runs short, the companies supplying the resources could emerge as the biggest winners. That’s why it’s essential for investors to consider the bottlenecks forming within the AI industry.

So today, I’ll examine the two growing constraints of AI, how they may influence which companies will thrive, and the proper ways to invest in them.

Where AI Is Hitting Its Limits

Let’s start with what makes the AI Revolution go ’round: Energy. 

Data centers are filled with expensive chips from companies like Nvidia Corp. (NVDA) and Advanced Micro Devices Inc. (AMD). But those chips must be powered to do any work… otherwise they are just pricey doorstops.

In other words, power isn’t just important to AI growth. It is AI growth. And it has become one of AI’s biggest bottlenecks. 

Demand for power near data centers is already straining local grids. In some areas, electricity now costs up to 267% more than it did five years ago. That means the next AI winners may not just be the companies building smarter machines, but the companies supplying the energy needed to run them.

Meeting this demand will require an all-hands-on-deck approach. That means wind, solar, nuclear, and natural gas. Hyperscalers like Microsoft Corp. (MSFT), Alphabet Inc. (GOOGL), and Amazon.com Inc. (AMZN) are already investing in nuclear, natural gas, and other dedicated power sources to guarantee electricity for future AI infrastructure. For example…

• Microsoft signed a 20-year deal to buy electricity from the planned restart of Three Mile Island nuclear plant in Pennsylvania.
• Alphabet partnered with Kairos Power to develop electricity from small modular reactors (SMRs).
• Amazon is investing $20 billion in Pennsylvania AI data centers, including a campus near the Susquehanna nuclear plant to secure the power needed for AI.

Electricity is clearly becoming a competitive advantage. But it’s only one chokepoint. The next bottleneck is something every AI system needs to function…

What Every AI System Needs

It needs memory, also known as DRAM.

Without enough DRAM, AI systems simply run out of room to process information. And the shortage may persist for years. Nearly 100 gigawatts of new data centers are scheduled to come online over the next four years. But there’s only enough DRAM to support roughly 15 gigawatts over the next two years. 

Without memory, artificial intelligence literally can’t think. 

Nvidia CEO Jensen Huang put it plainly: “The memory bottleneck is severe.” 

And Elon Musk just announced in Space Exploration Technologies Corp.’s (SPCX) first earnings report: “The limiting factor currently is memory.”

So, don’t just take it from me. Take it from the titans of the AI industry.

These bottlenecks are very real, and they will affect how the AI investing unfolds. But it is still missing a key piece; energy and memory are only two constraints.

The Bottleneck Blueprint

This isn’t the first time technology has created a shortage of essential resources. The same pattern appeared during the dot-com boom – when the internet’s rapid expansion created unexpected winners beyond the companies building the digital world.

The explosion of internet infrastructure, personal computers, and networking hardware meant the world suddenly needed far more metals than usual. I’m talking about copper… tantalum… germanium… and other essential ingredients to build the physical internet.

But mining and refining capacity couldn’t expand overnight. The result was a classic supply bottleneck. But investors who anticipated which resources would become scarce had the chance to profit in extraordinary ways.

From 1998 to 2001, I recommended four mining stocks to my readers that went on to generate remarkable gains. These companies became the quiet winners of the late-1990s tech boom.

One of them was Antofagasta plc (ANTO.L), which had become a copper-focused mining company.

I recommended Antofagasta to my readers on December 18, 1998 – about a year before the mine began production.

• Over the next three years, the stock soared 205%, while the S&P 500 was essentially flat.
• Over six years, Antofagasta delivered an astonishing 778% gain, while the S&P continued to nurse its losses, down 27%!

Antofagasta solved the puzzle before most investors even saw the clue. It built capacity during the investment phase of the 1990s – then benefited enormously once the metals bottleneck tightened.

That’s the power of identifying bottlenecks early. Now, we have the opportunity to apply this strategy again.

The Hidden Clues Behind AI’s Next Winners

The word limited is only the first clue in the AI investment puzzle. To find the biggest opportunities, investors need to solve four more:

If you want to know the answers to these questions, check out my free Market Shock presentation, where I dive even deeper into AI’s physical limitations: energy, memory, and the third bottleneck that could shape the next wave of AI winners.

I also reveal the types of companies that could benefit most from these constraints, including 15 free stocks – ticker symbols and all – that I believe are positioned to profit from the AI shortage problem.

Understanding AI’s power is essential when choosing stocks for your portfolio. But every great puzzle has hidden clues. By identifying the bottlenecks holding AI back, investors can uncover the companies positioned to benefit most from solving them.

Click here to learn how.

Regards,

Eric Fry

The post Scarcity Is the New AI Trade appeared first on InvestorPlace.

Where are these companies going to get everything they need to power it?

Demand for AI is surging so quickly that supplies of critical resources – from electricity to memory – are struggling to keep pace. And when demand overwhelms supply like this, it can create some very interesting opportunities for investors.

That’s exactly the kind of shift Eric has spent his career looking for. And he believes we’re seeing one take shape right now.

Below, he’ll show you why AI’s biggest bottlenecks could point toward its next big winners.

And for the full picture – including another major bottleneck he’s watching and the names and tickers he believes could benefit – check out Eric’s latest free Market Shock presentation.

I’ll let Eric take it from here…

*****************

Hello, Reader.

In a crossword puzzle, every answer connects. Solve one clue, and another piece suddenly falls into place.

Here’s one: Three words investors hate to see: “supply is ____”

Seven letters across. One answer.

Limited.

That word is becoming one of the most important clues in the AI investment puzzle.

The world wants more AI – more chips, more servers, more electricity, more data centers. But the supply of these critical resources is failing to keep up with demand.

And when supply runs short, the companies supplying the resources could emerge as the biggest winners. That’s why it’s essential for investors to consider the bottlenecks forming within the AI industry.

So, in today’s Smart Money, I’ll examine the two growing constraints of AI, how they may influence which companies will thrive, and the proper ways to invest in them.

Where AI Is Hitting Its Limits

Let’s start with what makes the AI Revolution go ’round: Energy. 

Data centers are filled with expensive chips from companies like Nvidia Corp. (NVDA) and Advanced Micro Devices Inc. (AMD). But those chips must be powered to do any work… otherwise they are just pricey doorstops.

In other words, power isn’t just important to AI growth. It is AI growth. And it has become one of AI’s biggest bottlenecks. 

Demand for power near data centers is already straining local grids. In some areas, electricity now costs up to 267% more than it did five years ago. That means the next AI winners may not just be the companies building smarter machines, but the companies supplying the energy needed to run them.

Meeting this demand will require an all-hands-on-deck approach. That means wind, solar, nuclear, and natural gas. Hyperscalers like Microsoft Corp. (MSFT), Alphabet Inc. (GOOGL), and Amazon.com Inc. (AMZN) are already investing in nuclear, natural gas, and other dedicated power sources to guarantee electricity for future AI infrastructure. For example…

• Microsoft signed a 20-year deal to buy electricity from the planned restart of Three Mile Island nuclear plant in Pennsylvania.
• Alphabet partnered with Kairos Power to develop electricity from small modular reactors (SMRs).
• Amazon is investing $20 billion in Pennsylvania AI data centers, including a campus near the Susquehanna nuclear plant to secure the power needed for AI.

Electricity is clearly becoming a competitive advantage. But it’s only one chokepoint. The next bottleneck is something every AI system needs to function…

What Every AI System Needs

It needs memory, also known as DRAM.

Without enough DRAM, AI systems simply run out of room to process information. And the shortage may persist for years. Nearly 100 gigawatts of new data centers are scheduled to come online over the next four years. But there’s only enough DRAM to support roughly 15 gigawatts over the next two years. 

Without memory, artificial intelligence literally can’t think. 

Nvidia CEO Jensen Huang put it plainly: “The memory bottleneck is severe.” 

And Elon Musk just announced in Space Exploration Technologies Corp.’s (SPCX) first earnings report this past week: “The limiting factor currently is memory.”

So, don’t just take it from me. Take it from the titans of the AI industry.

These bottlenecks are very real, and they will affect how the AI investing unfolds. But it is still missing a key piece; energy and memory are only two constraints.

The Bottleneck Blueprint

This isn’t the first time technology has created a shortage of essential resources. The same pattern appeared during the dot-com boom – when the internet’s rapid expansion created unexpected winners beyond the companies building the digital world.

The explosion of internet infrastructure, personal computers, and networking hardware meant the world suddenly needed far more metals than usual. I’m talking about copper… tantalum… germanium… and other essential ingredients to build the physical internet.

But mining and refining capacity couldn’t expand overnight. The result was a classic supply bottleneck. But investors who anticipated which resources would become scarce had the chance to profit in extraordinary ways.

From 1998 to 2001, I recommended four mining stocks to my readers that went on to generate remarkable gains. These companies became the quiet winners of the late-1990s tech boom.

One of them was Antofagasta plc (ANTO.L), which had become a copper-focused mining company.

I recommended Antofagasta to my readers on December 18, 1998 – about a year before the mine began production.

• Over the next three years, the stock soared 205%, while the S&P 500 was essentially flat.
• Over six years, Antofagasta delivered an astonishing 778% gain, while the S&P continued to nurse its losses, down 27%!

Antofagasta solved the puzzle before most investors even saw the clue. It built capacity during the investment phase of the 1990s – then benefited enormously once the metals bottleneck tightened.

That’s the power of identifying bottlenecks early. Now, we have the opportunity to apply this strategy again.

The Hidden Clues Behind AI’s Next Winners

The word limited is only the first clue in the AI investment puzzle. To find the biggest opportunities, investors need to solve four more:

If you want to know the answers to these questions, check out my free Market Shock presentation, where I dive even deeper into AI’s physical limitations: energy, memory, and the third bottleneck that could shape the next wave of AI winners.

I also reveal the types of companies that could benefit most from these constraints, including 15 free stocks – ticker symbols and all – that I believe are positioned to profit from the AI shortage problem.

Understanding AI’s power is essential when choosing stocks for your portfolio. But every great puzzle has hidden clues. By identifying the bottlenecks holding AI back, investors can uncover the companies positioned to benefit most from solving them.

Click here to learn how.

Regards,

Eric Fry

Editor, Smart Money

The post These Shortages Could Fuel AI’s Next Winners appeared first on InvestorPlace.

Arab oil producers announced an embargo on the United States – and almost overnight, the world’s most powerful economy was brought to its knees. Oil prices roughly quadrupled. Gas lines stretched for blocks. Washington imposed a national 55-mph speed limit to ration fuel. And the shock helped usher in a decade of stagflation that scarred an entire generation of investors.

The embargo itself lasted barely five months. The lesson lasted 50 years: a critical dependency, concentrated in the hands of a rival, is a weapon waiting to be fired.

I bring this up because history is rhyming right now.

Except this time, the chokepoint is a handful of obscure elements at the bottom of the periodic table. And the first shots of the new embargo have already been fired.

This past June, China’s Ministry of Commerce formally added several U.S. companies to its export-control and government-procurement blacklists – direct retaliation for America’s push to build a rare earth supply chain outside Beijing’s borders. It wasn’t the first warning, either. During the ‘Liberation Day’ tariff standoff, China restricted rare earth exports and sent automakers and defense contractors scrambling. Tesla (TSLA) faced multi-week production delays over Chinese export licenses.

Oil made the 20th-century economy move. Rare earth magnets make the 21st-century economy move. Let me show you why – and how investors can get on the right side of the divide.

Rare Earth Magnets Are the Hidden Input Behind Physical AI

The AI boom is no longer just about data centers and chatbots. This technology is going physical. And physical AI runs on motors.

Humanoid robots like Tesla’s Optimus are powered by a network of small electric motors in their shoulders, elbows, wrists, fingers, hips, knees, and ankles – reportedly dozens of precision motors per machine. The key ingredient inside nearly every one is a neodymium-iron-boron (NdFeB) magnet, which delivers exceptional strength in a compact, battery-friendly package. Each humanoid could contain 2 to 4 kilograms of rare earth magnets – sometimes more than an entire EV.

But robots are just the beginning. Consider how much of the modern buildout funnels through this single input:

• Tesla’s vehicles need those same magnets in the traction motors that turn electricity into forward motion. 
• Orbital data centers need them in the reaction wheels that point satellites without burning fuel. 
• Advanced semiconductor tools need them in the wafer-handling robotics that move silicon through fabrication.
• And virtually every guided munition, drone, and defense platform in the U.S. arsenal needs them, too.

Robots. Cars. Satellites. Chips. Different revolutions – same input.

The analysts running the numbers see what we see: from Bloomberg to McKinsey to Goldman Sachs, forecasters expect global rare earth magnet demand to roughly triple by 2040, led overwhelmingly by robotics and EVs.

So, for physical AI, more robots means more motors, more motors means more magnets, and more magnets means massive new demand for rare earth elements like neodymium, praseodymium, dysprosium, and terbium.

This supply chain starts in the dirt. And that’s exactly where the problem begins.

China Controls Roughly 90% of Rare Earth Magnet Production

When we first covered this story last summer, China controlled over 85% of the world’s rare earth refining and magnet production. Today, the picture is even starker. China produces the overwhelming majority of the world’s heavy rare earth elements – and roughly 90% of the finished magnets made from them.

Read that again. The single input underpinning robotics, EVs, satellites, chip fabs, and modern defense systems is controlled – almost in its entirety – by America’s chief strategic rival. A rival that has now demonstrated, repeatedly, that it’s willing to weaponize that position.

In 1973, at least the oil weapon was pointed at us by a coalition of nations with mixed motives and leaky discipline. This time, the chokehold belongs to one government.

Washington has finally gotten the message. The U.S. is investing billions in domestic mining, refining, and magnet-making, backed by Defense Production Act funding, DOE grants, and tariff protection. 

And defense acquisition rules now require contractors to phase out Chinese-origin rare earth magnets by January 2027 – a hard regulatory clock forcing a large pool of manufacturers to find non-Chinese supply on a fixed timeline.

Which raises the trillion-dollar question: find it where?

MP Materials Is Building America’s Mine-to-Magnet Alternative

Right now, there is exactly one American company that can mine, refine, and manufacture rare earths into finished magnets at commercial scale: MP Materials (MP).

MP owns Mountain Pass in California – the largest rare earth mining site in the Western Hemisphere, accounting for more than 10% of global supply. And just look at what has happened since we first profiled the company.

The Pentagon’s $400 million investment turned out to be far more than a cash infusion. The U.S. government took a 15% equity stake and signed a 10-year offtake agreement for magnet materials at a guaranteed price floor of $110 per kilogram. Even if global rare earth prices crash – the kind of move China could try to engineer to undercut Western producers – MP has a decade of government-backed economics on a meaningful portion of its output. That kind of downside protection is nearly unheard of for a commodity-adjacent business.

Apple, GM, and the Pentagon Are Validating the Buildout

Since then, the validation has kept stacking up. Apple (AAPL) signed a $500 million agreement to buy American-made rare earth magnets from MP, with a dedicated recycling program feeding its Fort Worth, Texas facility. General Motors (GM) has a long-standing supply agreement for EV traction motors. The company formed a joint venture with the U.S. government and Saudi Arabia’s state mining company to develop a rare earth refinery in the Kingdom – a second leg of supply outside both China and its domestic operations. Its “10X” expansion plan targets nearly 10,000 metric tons of annual magnet production by 2028, roughly a tenfold increase from a couple of years ago. And it’s commissioning heavy rare earth separation at Mountain Pass – the capability to isolate elements like dysprosium and terbium, essential for magnets that hold their strength inside a hot robot joint or satellite actuator.

The business is showing it, too. First-quarter 2026 revenue jumped 49% year-over-year to $90.6 million, well ahead of Wall Street estimates, as the company’s first commercial magnet shipments began scaling.

And one more telling detail: MP stock pulled back nearly 30% in July – a slide triggered when China’s Ministry of Commerce put the company on that export-control blacklist. But look at what happened next. The stock has already clawed its way back to where it traded before the news. 

Beijing considered this company important enough to sanction. The market read it as a risk for about five minutes, then recognized it for what it really was: confirmation. 

Why MP Materials Sits Beneath the Physical AI Buildout

Humanoid robots. Electric vehicles. Satellites and orbital data centers. Advanced chip fabs.

Those are the four pillars of one man’s empire.

Every one of Elon Musk’s biggest bets – Optimus, Tesla’s vehicle fleet, SpaceX‘s (SPCX) orbiting constellations, and his push into chipmaking – funnels through the exact same magnet supply chain we’ve spent this whole issue dissecting. History’s most ambitious industrial plan has a single point of failure, and it’s sitting at the bottom of the periodic table.

Now, one honest caveat, because we deal in facts here, not hype: no supply agreement between MP and Tesla or SpaceX has been announced. The connection is structural – shared inputs, shared strategic goals – not a signed contract. But a manufacturer as famously obsessed with controlling his own inputs as Musk, ramping Optimus toward volume production, drawing on the same domestic magnet source that Apple and GM already depend on? We wouldn’t bet against it.

Either way, the takeaway is the same: whoever supplies the magnets supplies the empire.

The Bottom Line: Rare Earth Stocks Are Becoming a National-Security Trade

The 1973 embargo caught America flat-footed. But the investors who understood the chokepoint before the weapon fired didn’t just avoid the pain – they rode the energy supercycle that followed to generational wealth.

Today’s chokepoint is rare earth magnets. The weapon has already been test-fired. The regulatory clock is ticking toward January 2027. And the biggest industrial buildout of our lifetimes – Musk’s included – is competing for the same limited supply.

You can see the whole board before the market does. The only question is what you do with it.

Here’s my answer.

I’ve spent months mapping how every pillar of Elon Musk’s next act – the robots, the orbital data centers, the chip fabs, all of it – depends on a short list of critical suppliers. I call the master plan “XPANSE.” And it’s a project so enormous that Elon himself believes it could make early investors 1,000 times their money.

In my new briefing, I explain why this buildout could help America eliminate a looming threat one high-ranking government official has dubbed “an economic apocalypse”… 

I lay out the three steps you must take today to get on the right side of this shift… 

And I give away the name and ticker symbol of an investment perfectly positioned to capitalize – free.

Don’t wait for the gas lines to form.

Watch the full XPANSE briefing now.

The post China Targeted MP Materials for a Reason appeared first on InvestorPlace.

This week, Digest writer Jeff Remsburg is on vacation. But don’t worry – the Digest isn’t going anywhere.

While he’s out, we’ll go straight to our experts, letting them share the ideas they’re most fired up about with you.

Think of it as a guest-editor week, but with the same mission as always: to bring you the insights, analysis, and stock ideas that matter most to your portfolio.

Today, we’re kicking things off with senior analyst Brian Hunt, editor of Money & Megatrends. If you’re not familiar with Brian’s work, he focuses on the powerful trends shaping tomorrow’s biggest investment opportunities – then translates them into practical, actionable ideas that investors can implement today.

The issue below from last Tuesday is a great example. Brian highlights several themes he’s watching closely, shares a handful of stocks that have caught his attention, and explains what recent market action may be telling us about where the economy is headed next.

Best of all, Money & Megatrends is completely free and lands in subscribers’ inboxes every day the market is open. If you enjoy today’s issue, just click here to sign up for free.

Enjoy!

Four actionable stock ideas from a legendary investor … the AI Power theme keeps its momentum … the American consumer is sending this stock higher…

Over the past 12 months, the S&P Biotech ETF (XBI) is up 72%, GLP-1 drug giant Eli Lilly (LLY) is up 48%, and the world’s largest healthcare ETF, the Health Care Select Sector Fund (XLV), is up 23%.

In other words, our call to invest in Boomer health care and the related trend in biotechnology is paying off well.

Constant Money & Megatrends readers know the bull case here: The giant Baby Boomer demographic is entering the phase of life when healthcare spending skyrockets. For many boomers, a typical month involves going to see at least one doctor to have something looked at, removed, or treated. This means many healthcare businesses are experiencing huge demand now – and will for at least the next decade.

Now is a good time to look at how Stanley Druckenmiller is positioning himself to benefit from this megatrend.

Druckenmiller is one of the world’s greatest investors. He’s on my “Mt. Rushmore” of investors and traders. It’s been reported that “Druck” achieved 30% annual returns for 30 years without a single down year. That earns him his own wing in the Wall Street Hall of Fame.

In recent interviews, Druckenmiller has mentioned he’s bullish on health care and biotech… especially given how diagnostics, analytics, and treatment discoveries could be turbocharged by the pairing of AI and genomics. He employs specialized experts in the field to perform research and find stock ideas.

Large money managers like Druckenmiller must report their public-market positions to government regulators via “13F filings.” Those filings are made every quarter and are public. 13F filings essentially allow you to look over the shoulder of investors like Druckenmiller, which is often useful for spotting trends and good stock ideas. Reviewing their new buys is like having a world-class research team working for you for free.

With all this in mind, we researched Druckenmiller’s recent stock buys in the healthcare sector and found four stocks with compelling long-term outlooks:

Caris Life Sciences (CAI) is a $4.4 billion market cap oncology diagnostics company. It analyzes the molecular characteristics of patients’ tumors using DNA, RNA and protein information, helping physicians select treatments and clinical trials that will be appropriate for a particular cancer. Caris also uses its large clinical and molecular database to support pharmaceutical research and drug development. Its opportunity rests on expanding cancer testing, increasingly personalized treatments and the growing value of real-world oncology data.

Option Care Health (OPCH) is a $3.5 billion market cap provider of home and alternate-site infusion therapy. It delivers medications, nursing services and clinical support to patients receiving treatments for immune disorders, infections, cancer, and other complex conditions. Home infusion is generally less expensive and more convenient than hospital-based treatment. Option Care benefits from an aging population, growing use of specialty biologic drugs and pressure to move care into lower-cost settings.

Olema Pharmaceuticals (OLMA) is a $985 million firm developing treatments for hormone-receptor-positive breast cancer. Its lead drug, palazestrant, is an oral therapy designed to completely antagonize and degrade the estrogen receptor, including mutated forms that can cause resistance to existing treatments. Olema is studying the drug alone and in combinations with other cancer medicines.

Belite Bio (BLTE) is a $6.2 billion market-cap clinical-stage biotechnology company developing a treatment for retinal diseases associated with toxic vitamin-A byproducts. Its principal targets include Stargardt disease, a rare inherited condition that can cause progressive vision loss, and geographic atrophy related to dry age-related macular degeneration.

Druckenmiller believes the fundamentals detailed above are creating a significant opportunity in healthcare. He has the money to buy world-class research and perform in-depth analysis. The stock ideas above are the product of all this. In a health care bull market, it’s valuable information.

A major earnings report shows our Power Grid theme is a juggernaut. Are you profiting?

It’s official: Eaton’s (ETN) business is booming.

And that’s important for you and your portfolio.

The company reported earnings at the end of July that beat Wall Street’s expectations. It also reported strong sales growth and an enormous backlog of future orders. After the news, Eaton’s stock jumped 5.5% to a new all-time high.

Why should you care about any of this?

Eaton is one of the largest companies that most people don’t know about.

With a market cap of $170 billion, over 95,000 employees, and annual revenue of $27.4 billion, Eaton is a giant of American manufacturing.

The company makes electrical transformers, circuit breakers, utility voltage regulators, switches, electrical panels, and other critical components of a functioning power grid. Its fastest-growing segment equips AI data centers with the electrical infrastructure they need to operate.

Money & Megatrends readers in good standing know the compelling “bull case” for stocks in the electrical infrastructure sector.

Given AI’s enormous promise, large tech firms like Google (GOOG), Microsoft (MSFT), and Amazon (AMZN) are investing trillions of dollars to build the best AI models and infrastructure. Much of this money is being spent on massive data centers.

All that AI infrastructure is poised to consume huge amounts of electricity. Goldman Sachs forecasts global data center power demand will climb 50% by 2027 and as much as 165% by the end of the decade.

This is creating a big investment opportunity.

The U.S. power grid is often called the world’s largest machine. It’s a giant network of power stations, transmission lines, substations, and underground wires. Most people barely know it’s there or how it works, but without this big machine, your lights don’t turn on, there’s no Netflix, and your iPhone doesn’t charge.

Industry experts say the power grid is aging and creaking under the strain of increased electricity demand. The American Society of Civil Engineers (ASCE) gave the energy sector a D+ in its 2025 Infrastructure Report Card, citing concerns about rising energy demand, aging infrastructure, and a lack of transmission capacity.

Soaring electricity demand… a grid badly in need of an upgrade… AI supremacy on the line… trillion of dollars of economic output on the line…

This is a recipe for a bull market in companies that build, repair, and upgrade our power grid. Investment plans for 51 investor-owned utilities total an estimated (and gigantic) $1.4 trillion over the next five years, according to PowerLines, an advocacy group. We are talking about large, relentless flows of money into this industry.

In our July 31 issue, we analyzed the long-term trend in the “Power Grid Upgrade” theme and reaffirmed our bullish stance. Eaton’s strong results reinforce our thinking.

Big tech is spending trillions of dollars on the AI infrastructure buildout. AI supremacy versus China is on the line. Plus, the Made in America megatrend we are bullish on will require huge amounts of reliable electric power.

Given the tremendous amount of money and geopolitical power at stake here, the Power Grid Upgrade theme is going to see huge money flows over the next five years. With this bullish backdrop in mind, I believe top Power Grid Upgrade stocks will be higher two years from now than where they are now.

A major retailer soars to a new high. Are you heeding its message?

If you think the American consumer is struggling, think again.

Williams-Sonoma (WSM) just hit an all-time high.

The stock is up 25% over the past year.

Such a company doesn’t enjoy boom times when the American consumer is pulling back. And there’s insight for investors to take from this development.

Williams-Sonoma is one of America’s largest furniture, décor, and “all things kitchen” retailers. It operates through its popular Pottery Barn, West Elm, and Williams-Sonoma stores.

With a huge-for-a-specialty-retailer market cap of $29 billion and over 600 stores across the country, WSM is a pervasive presence in America’s shopping malls and homes.

Not in all homes, however.

WSM sofas, chairs, kitchenware, cabinets, and beds on are the pricier side of their markets. They aren’t on the super-high end, but they most certainly are not IKEA.

Most WSM offerings are considered “accessible premium.” The company targets mid to high-end consumers who can drop $10,000+ on a bedroom set or $1,000 on pots and pans.

This year, I’ve written over a dozen research notes detailing how many consumer spending stocks, such as WSM and Starbucks (SBUX), are signaling the American consumer is alive and well. This impressive market action is in stark contrast to mainstream media reports citing the popular but flawed Michigan Consumer Sentiment Survey and its dismal consumer sentiment readings.

I’ve been investing and reading financial research for 28 years. During all that time, I’ve heard many famous pessimists forecast the death of the American consumer. Well, not even the dot.com crash or the 2008 financial crisis could knock it out.

This is why I say that in the event of global thermonuclear war, two things will survive. Cockroaches and the American consumer.

As an investor, you can base your decisions on bearish stories written by journalists who don’t know a bull market from a flea market. You can base your decisions on forecasts issued by professional pessimists who predict nothing but doom and gloom.

Or, you can focus on reality. You can focus on what’s happening in the real world, like with Williams-Sonoma…

Right now, reality says consumer stocks are in an uptrend, and the consumer is doing just fine.

Invest accordingly!

Regards,

Brian Hunt
Editor, Money & Megatrends

The post Four Actionable Stock Ideas From a Legendary Investor appeared first on InvestorPlace.

Three founders of the world’s leading AI companies walk into a bar…

One says, “We’re in a new era of rapidly improving AI.”
Another says, “We’re only at the beginning.”
The third says, “AI is already superhuman at many things.”

It sounds like the setup for a bad joke. But here’s the punchline: The people building the technology believe AI’s biggest transformation is still ahead of us.

OpenAI CEO Sam Altman, outgoing Google DeepMind CEO Demis Hassabis, and Tesla Corp. (TSLA) CEO Elon Musk have all been discussing the possibility of a dramatic leap in AI capabilities (bar not pictured):

• In the Relentless podcast last month, Altman said “I’ve been waiting for this my whole life.”
• Musk recently echoed the same view on X.
• And Hassabis published a Substack essay outlining how the world may be approaching a major new AI breakthrough.

At the heart of their vision is a powerful feedback loop: When AI becomes better, it can design even better AI models itself, and so on indefinitely.

Well, that loop is already beginning.

In June, Anthropic CEO Dario Amodei said that Claude is increasingly helping engineers write code, test ideas, and improve AI models – thereby accelerating the pace that new systems can be developed.

And this feedback loop could accelerate dramatically with the arrival of artificial general intelligence (AGI). This is when AI becomes as smart as humans.

Hassabis’s essay, mentioned above, explains why it’s so important:

This is a pivotal moment in human history. Artificial General Intelligence (AGI), a system that exhibits all the cognitive capabilities the brain has, is probably only a few short years away.

The magnitude of this technology’s impact will be unprecedented, perhaps 10x of the Industrial Revolution at 10x the speed.

But AGI won’t be just another tool. It will likely become a system that contributes to its own advancement.

For companies, that could mean surging demand for the infrastructure needed to power AI.

And there are already signs that this transformation is underway. OpenAI recently made a breakthrough that offers a glimpse of what’s ahead.

So, in today’s Smart Money, I’ll look at the signs that AI is moving toward AGI – and which companies are helping make that future possible.

AI Is Learning to Learn

OpenAI recently reported that its GPT-5.6 Sol model could improve its reasoning over time.

But first, a little context.

ARC-AGI-3 is a benchmark designed to test the type of intelligence that matters for AGI: adaptation.

Unlike a traditional test where an AI answers questions based on what it already knows, ARC-AGI-3 puts it in unfamiliar environments and assesses whether it can explore unfamiliar environments, learn from experience, build internal models, and plan actions.

In other words, it tests whether AI can learn how to solve new problems – something much closer to how humans learn.

Two weeks ago, the company found that its GPT-5.6 Sol model was much smarter than the benchmark originally suggested. By changing two system settings, the model was able to preserve parts of its earlier thought process during long tasks, similar to how we use notes. It was then able to build on that earlier reasoning to improve its performance.

That may sound like a small technical improvement. But it points to something much bigger…

AI systems are becoming better at adapting over time and demonstrating capabilities that could bring us closer to AGI.

OpenAI’s recent breakthrough suggests the next AI leap may come from systems that can remember, reason, and improve over time.

To turn it back to Hassabis:

AGI has the potential to be the ultimate tool for advancing science and medicine, and to drive enormous productivity gains and economic growth.

If AI reaches human-level intelligence, the biggest investment opportunity may not be the companies building AI models — but the companies supplying the chips, energy, memory, and materials needed to scale that intelligence.

Hassabis mentions a “precious window before AGI arrives.” For investors, that window could be an opportunity to get ahead of the infrastructure boom needed to power the next era of superintelligence.

Intelligence may be digital, but scaling it is a physical resource problem. The world cannot reach AGI simply by writing better software. It needs enough physical resources to run that software.

And that starts with the chips themselves.

Here’s the Punchline…

One company I’ve got my eye on is PDF Solutions Inc. (PDFS).

PDF Solutions helps semiconductor companies produce more usable chips from every manufacturing run. In simple terms, it helps chipmakers make more good chips.

PDF’s software identifies defects, improves manufacturing yields, and helps chipmakers reduce costly failures. Those capabilities become even more valuable when AI chips are in short supply and every usable chip counts.

If AI advances toward AGI, it could dramatically increase the amount of computing the world needs. As manufacturers race to increase chip production, companies like PDF could benefit from the growing pressure to maximize chip production.

The world’s leading AI builders all believe AI is entering a new phase where it learns, reasons, and improves more rapidly. If they’re right, every leap in AI capability will require even more physical infrastructure – making the suppliers of chips, memory, power, and data centers some of the biggest winners.

That is why, in my new free Market Shock presentation, I reveal 15 companies across the raw materials, energy, and memory spaces that I am watching very closely.

These companies, like PDF, are the picks-and-shovels providers behind the AI buildout. They may not be household names, but they could play an essential role in supplying the physical infrastructure required to power the next phase of AI.

And that, folks, is no joke.

Click here to access these companies – ticker symbols and all – for free.

Regards,

Eric Fry

The post What 3 AI Billionaires See Coming and the Stock to Invest in Before It Arrives appeared first on InvestorPlace.

SanDisk Corporation (SNDK) reported fourth-quarter earnings of $39.25 per share, easily topping analysts’ expectations of $34.51 per share. Revenue surged 372% year-over-year to $8.97 billion, also beating estimates of $8.5 billion.

Those are the kinds of numbers that should send a stock higher. Instead, SanDisk shares fell 6.8% on Thursday – and another 3.7% on Friday.

Why? Well, SanDisk’s revenue outlook came in softer than expected.

SanDisk expects revenue between $10.3 billion and $10.8 billion for fiscal year 2027, while Wall Street was hoping for $10.82 billion.

But was that enough to justify the selloff after such a blowout quarter?

I don’t think that’s the whole story.

A growing number of investors seem convinced that the spectacular growth we’ve seen from AI-related companies simply can’t continue.

In other words, the better the numbers get, the more Wall Street worries that we’ve reached the peak.

But my guest on this week’s Navellier Market Buzz, Adam Johnson, thinks Wall Street has it backward.

Adam believes the recent weakness in semiconductor stocks was unwarranted, given the strength of corporate earnings. As he put it, the AI “freight train” is still gathering steam – and has not yet reached full speed.

I think he’s on to something. In fact, we cover why strong earnings aren’t always translating into higher stock prices – and whether Wall Street is underestimating just how much runway the AI boom still has left.

We also talk about where Adam sees opportunities as spending spreads into the power, storage and hardware needed to keep the AI buildout moving.

Click the image below to watch the latest episode of Navellier Market Buzz.

The Next Stop for the AI “Freight Train”

Adam said it best: The AI “freight train” is still gathering steam.

Demand for computing power continues to grow. Hundreds of new data centers are in the pipeline. And companies supplying the power, storage and hardware needed to keep them running are seeing extraordinary demand.

And here’s the important part…

If the AI freight train hasn’t even reached full speed yet, investors need to be thinking about where it’s headed next.

Because I believe the next stage of the AI boom could look very different from the one that made NVIDIA Corporation (NVDA) a household name.

Today’s AI boom is already putting enormous pressure on the infrastructure needed to support it. And an even more ambitious computing buildout is taking shape right now…

It involves a massive new computing initiative being assembled across the Department of Energy’s national laboratories – one designed to accelerate scientific breakthroughs in AI, energy, medicine and more.

I call it the AI Reset of 2026.

I put together this special presentation explaining what I believe it could mean for today’s AI leaders – along with the companies I believe could benefit most as this next phase unfolds.

Click here to watch it now.

Sincerely,

Louis Navellier

Editor, Market 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

NVIDIA Corporation (NVDA) and SanDisk Corporation (SNDK)

The post Why the AI “Freight Train” Is Still Gathering Steam appeared first on InvestorPlace.

This Week’s Ratings Changes:

Upgraded: Strong to Very Strong

Downgraded: Very Strong to Strong

Upgraded: Neutral to Strong

Downgraded: Strong to Neutral

Upgraded: Weak to Neutral

Downgraded: Neutral to Weak

Upgraded: Very Weak to Weak

Downgraded: Weak to Very Weak

To stay on top of my latest stock ratings, plug your holdings into Stock Grader, my proprietary stock screening tool. But, you must be a subscriber to one of my premium services.

To learn more about my premium service, Growth Investor, and get my latest picks, go here. Or, if you are a member of one of my premium services, you can go here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Eli Lilly Upgraded, Best Buy Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

BlackSky (BKSY) was down almost 20%. Rocket Lab (RKLB), AST SpaceMobile (ASTS), and Planet Labs (PL) shed more than 30%. Even SpaceX (SPCX) – fresh off the largest IPO in history – slid over 50% from its June 16 record close.

But here’s what makes this moment so interesting: while the stocks were selling off, the businesses were doing the exact opposite.

BlackSky just reported 50% year-over-year revenue growth and swung to positive adjusted EBITDA. Redwire (RDW) posted record revenue – up nearly 90% year-over-year – with gross margins flipping from deeply negative to nearly 28%, and a record $542 million backlog. And SpaceX’s first-ever public earnings report showed revenue up 92%, with its AI segment growing 247%.

That’s a dislocation. Prices went one way while fundamentals went the other. And now, these beaten-down names are showing early signs of reversal.

We think they’ve still got miles of orbital runway left.

Why? Because the space economy is finally getting real. It’s no longer some far-off “Jetsons” fantasy.

Defense Spending Is Becoming a Growth Engine for Space Stocks

We’ll start with the national security angle first.

Governments are waking up to the uncomfortable fact that space is the new strategic battleground.

Satellites can now provide real-time battlefield intelligence, secure military communications, early warning missile detection, navigation and targeting systems, and surveillance on rival (and even friendly) nations.

Just look to Ukraine – its military would likely have been wiped off the map without Starlink – or China, which now considers satellite dominance a national priority.

Even the Pentagon has created a $30-plus billion annual budget line called the U.S. Space Force.

This is a long-term arms race – one that favors nimble, responsive space companies with launch capacity, satellite imaging capabilities, and hardware manufacturing.

The usual suspects benefit here:

• BlackSky, which provides real-time Earth intelligence for military and defense
• Planet Labs, operator of the largest constellation of Earth observation satellites
• Rocket Lab, launch provider for government payloads, hypersonic testing
• Palantir (PLTR), which offers analytics for satellite data

The bottom line? We estimate national defense TAM in space is about $30- to $40 billion today. But as intelligence demand and geopolitical tensions escalate, it could easily double over the next decade.

And it’s just one vertical of the multi-faceted Space Economy…

Satellite Internet Is Expanding the Space Economy

Another big vertical here is space-based communications because the entire communications industry is being rewritten from orbit.

The world is moving toward a space-powered internet: a global, always-accessible broadband network delivered from thousands of small satellites in low Earth orbit (LEO).

This is more than a theoretical future. It’s already in action:

• Starlink now has over 10,000 satellites in orbit and serves 12 million users worldwide.
• Amazon Leo (formerly dubbed Project Kuiper) continues building out its constellation to support AWS and global internet.
• AST SpaceMobile is going one step further, building the first cell tower in the sky that connects directly to your smartphone without dishes or terminals.

That’s a major step up, especially considering that 2.2 billion people worldwide still lack reliable internet access, and billions more suffer from poor mobile coverage.

Not to mention, we still don’t have cell coverage on airplanes. And natural disasters like earthquakes, fires, and tsunamis often knock out cell coverage when we need it most.

That’s why we think the total addressable market here is huge. We see it climbing toward $150 billion by 2035 – possibly much more if these constellations become the backbone for rural broadband, global telecom, and even cloud connectivity.

Who benefits?

• ASTS – offers direct satellite-to-phone coverage in partnership with AT&T, Vodafone, and Telefonica
• RKLB – launching communications satellites for multiple players
• PL & BKSY – may support telecom mapping, planning, and routing
• SpaceX – now public after the largest IPO in financial history, giving retail investors direct access to the most dominant player in the space economy for the first time

Between national defense and communications, we’re already staring at a $50- to $65 billion market in space today.

And it’s still very early days.

Orbital Data Centers Could Become the Space Economy’s Biggest New Market

Here’s the vertical that didn’t exist when we first started writing about the space economy – and it may end up being the biggest of them all.

AI’s growth is running into hard physical limits on Earth. Data centers need enormous amounts of land, power, and water – and communities increasingly don’t want them nearby. Lawmakers in at least 14 states have introduced legislation to restrict new data center construction.

Space solves all three problems at once. Orbital data centers harvest uninterrupted solar power around the clock, require zero land, and radiate waste heat directly into the vacuum of space – no water needed.

The ‘land grab’ has already begun. SpaceX has filed with the FCC to launch up to one million orbital data centers. Google has entered talks with SpaceX to expand its own space-based compute efforts. Anthropic has expressed interest in partnering on orbital AI capacity. And Jeff Bezos’ Blue Origin just asked the government for permission to launch more than 50,000 orbital data centers of its own.

Every one of those satellites needs launch capacity, solar arrays, specialized hardware, and in-orbit servicing. The companies supplying those pieces sit directly in the path of what could become a multi-trillion-dollar buildout.

Four More Space Economy Markets Investors Should Watch

This is all great news for RKLB, PL, BKSY, and ASTS. But those are likely just the first puzzle pieces to unlocking profits within the trillion-dollar space economy.

Earth Observation: Turning Satellite Images Into Intelligence

There’s Earth observation.

We’re entering the age of persistent planetary surveillance. Think:

• Monitoring crop yields (for commodity traders)
• Tracking cargo ships (for logistics and supply chains)
• Detecting oil spills, deforestation, wildfires, and droughts
• Verifying carbon emissions and ESG compliance

Governments, hedge funds, insurers, farmers, and climate groups all want this data.

PL and BKSY are two of the biggest players in this niche. They control massive constellations of satellites and sell high-frequency data with AI analytics on top.

TAM for this sector is expected to hit $20- to $30 billion by 2030.

Lunar Infrastructure: Building a Commercial Economy Around the Moon

There’s also space infrastructure.

Missions to the Moon. Telecom relays on lunar orbit. Bases on Mars. It all sounds sci-fi – until you realize NASA’s Artemis Program is already working on it.

The Moon is now an infrastructure hub for mining water ice (rocket fuel), telescopes (no light pollution), communication relays, and launching deeper-space missions.

Rocket Lab’s Photon satellite bus has already delivered a mission to lunar orbit. Other players like Intuitive Machines (LUNR) and Astrobotic are planning landers.

It might be niche today, but it’ll be potentially huge tomorrow.

Satellite Servicing: The Maintenance Layer of the Space Economy

There’s also in-space manufacturing because… let’s face it… why make stuff on Earth when microgravity offers the perfect conditions for making certain things? Like:

• ZBLAN fiber optics: 100x better transmission, only manufacturable in space
• Protein crystal growth: better drugs, vaccines, and biotech
• Semiconductors: zero-defect vacuum conditions

Startups like Varda Space are building in-space factories. Redwire is printing tools on the ISS. In fact, Rocket Lab is already launching some of these missions.

Tiny TAM today – but potential for $10- to $20 billion by 2040.

Space Servicing: Maintaining the New Orbital Economy

And then you have the whole satellite servicing market.

Satellites are expensive. They age, fail… and then crash, rendering them nothing more than junk. The solution therein?

• Servicing and refueling in orbit
• ‘Tugboats’ for moving satellites
• Bots to clean up space debris

This is like the equivalent of AAA for space. And we think it could be a $10-billion-plus market by the 2030s.

The Bottom Line: Space Stocks Are Still Early in a Much Bigger Economy

Put all this together – defense, communications, orbital compute, EO, infrastructure, manufacturing, servicing – and the total space economy TAM is already near $100 billion.

Depending on regulation and global policy, that number could stretch to unfathomable heights over the coming decades.

Now here’s the real kicker: outside of SpaceX, not many own this trade yet.

Planet Labs has a market cap of approximately $8 billion. AST SpaceMobile is right around $27 billion. And BlackSky is only valued at about $1 billion.

In terms of their addressable market, these are penny stocks with planetary potential.

Now, to be sure, not every company will win. Some will fizzle or get acquired. Some might crash and burn, literally.

But the winners will provide the foundational infrastructure for the next trillion-dollar economy. And as we saw during the early internet era, a single winner could 20X, 50X, even 100X in a decade.

So, the smartest approach here might be a simple one: buy a basket of them now. Don’t try to pick the single winner. Just be exposed.

Because if this space economy thesis plays out – and the signs are saying it’s already well underway – the upside will vastly outweigh any individual misfires.

There’s just one wrinkle to the basket approach.

For the first time, all the puzzle pieces I just described – launch, satellites, AI compute, robotics, manufacturing – are being assembled under a single roof, by a single man.

Elon Musk took SpaceX public in the largest IPO in history. He merged it with xAI. And now, virtually every Silicon Valley insider – from his own biographer to the president of SpaceX herself – expects him to complete the consolidation with the biggest merger of all time.

The estimates around what it could be worth are staggering – bigger than AI, robotics, clean energy, and driverless cars combined.

And just like the space stocks in this piece, the biggest gains won’t come from owning the giant at the center. They’ll come from the small, little-known suppliers riding its coattails – including one that trades for just $15 a share.

I’ve laid out the full story – and the three steps to get positioned – right here.

The post Space Stocks Crashed in July. Their Businesses Didn’t. appeared first on InvestorPlace.

Tom Yeung here with today’s Smart Money.

There is usually a “tuition cost” that comes with learning how to invest.

• That first stomach-churning loss…
• That first painful tax bill…
• That first accidental “buy” order instead of a “sell”…

Everyone remembers their early mistakes. It’s what makes you a better trader.

That’s because learning to invest by paper trading is like figuring out how to swim by reading a book. There is no substitute for diving in and trying not to drown.

Now, most of us pay that tuition a little at a time. Preferably very early on.

But one AI hedge fund appears to have paid a very expensive tuition bill in recent weeks.

I’m talking about Situational Awareness, an AI fund run by one of Wall Street’s brightest new stars, Leopold Aschenbrenner. The 24-year-old former OpenAI researcher first gained notice in 2024 after publishing a lengthy essay called “Situational Awareness: The Decade Ahead” that predicted the rise of artificial general intelligence (AGI).

Then Aschenbrenner put money behind that idea. He launched a hedge fund with the same name and built enormous positions around the AI boom.

For a while, the results looked almost supernatural. The fund gained 2,000% in 2025, and another 439% in the first half of 2026. Situational Awareness was worth $45 billion at its peak.

But then AI stocks hit a speed bump this summer.

Soon, the hedge fund began losing money. Then much more. So much, in fact, that it was forced to dump whatever it could. It ultimately sold its public-stock portfolio to a different hedge fund, Ken Griffin’s Citadel, notching an 80% loss.

In other words, Aschenbrenner had seen the AI future before almost everyone else…

But he had not built a portfolio that could survive the trip.

Fortunately, you don’t need a billion-dollar hedge fund – or a mountain of leverage – to profit from the AI Revolution.

Today, I’ll explain why simply being right about AI isn’t enough… lay out the two qualities I believe separate long-term winners from eventual blowups… and introduce you to one company I think fits that description.

Then, I’ll show you where you can find three more stocks that we’re watching…

The Right Thesis, The Wrong Trade

In fairness, I believe Aschenbrenner remains directionally correct about AI.

AI systems are becoming more capable. Businesses are spending hundreds of billions of dollars to build data centers and build better AI models. The AI Revolution will have many years of growth ahead.

However, a correct prediction is not automatically a good investment.

Imagine someone knowing in 1997 that the internet would transform the global economy. They would have been absolutely right. And if they had put their life savings into Amazon.com Inc. (AMZN), they would have made millions… if not billions of dollars. The stock is up more than 300,000% since its listing in 1997.

But what if that same investor had bought Pets.com instead? After all, Pets.com was also an early e-commerce player. Besides, it had a sock-puppet mascot that showed up in a Super Bowl ad and on Good Morning America. Jeff Bezos never thought of doing that!

Instead, Pets.com turned out to be a total disaster. The pet food delivery company could not figure out how to become profitable, and the stock went from an IPO price of $11 down to $0.19 before it was totally liquidated in 2001. Hundreds of employees lost their jobs, and investors were wiped out.

The same will be true of the AI Revolution. Not every AI firm will succeed, and some will fail spectacularly.

But that’s not really what doomed Situational Awareness. The fund’s biggest problem wasn’t that it believed in AI. It was that it used enormous leverage to amplify those bets. When AI stocks stumbled, even temporarily, those leveraged positions quickly became impossible to maintain.

That’s an important lesson for individual investors. You can be absolutely right about the future… and still lose money if you own the wrong companies, pay too much for them, or take on too much risk.

The Right Way to Play the AI Revolution

You’re probably now wondering how to separate the “Amazon.com successes” from the “Pets.com flops” of the AI Revolution.

I have some good news for you. In my experience, great businesses usually share a few common characteristics, even in industries moving as quickly as AI:

1. A wide business moat. Some AI companies own valuable technology and enjoy real pricing power. These are called “moats” because they protect those companies from competition. And they’re a key reason for a company’s long-term success.

2. The right price. The best investments are bought cheaply before everyone has discovered their worth. If a stock today is worth $1,000 per share, an investor would have made far greater profits if they had bought for $10… or $1… or better yet $0.10.

Those are two of the qualities that Eric looks for when researching AI investments.

He isn’t simply searching for “the next Nvidia” or “the next Amazon.” Even though there are some fantastic mega-cap AI companies out there, these stocks have already been discovered by just about every person on Earth with a working brokerage account.

In fact, if Amazon rose another 300,000% because of its AI business, it would be worth almost $9 quadrillion. If you spent $1 billion per day, it would take roughly 25,000 years to burn through that amount!

Nor is Eric trying to replicate the highly leveraged approach that helped Situational Awareness generate spectacular gains – and equally spectacular losses. Extraordinary returns are wonderful if you can keep them. But if your portfolio loses 80% every time the market hits a rough patch, you’re probably not going to stay in the game very long.

Instead, Eric focuses his search on a core group of companies that are building AI’s “Golden Rivets.” These are the specific, irreplaceable pieces needed to construct and power the AI buildout.

These Golden Rivet producers are not necessarily the companies receiving the loudest television coverage. Nor are they being bought up by the hottest AI hedge funds in town. In many cases, they are old-economy businesses that Wall Street overlooked while everyone chased chips and chatbots.

That is precisely what makes them interesting.

One example is Teradyne Inc. (TER). Rather than competing to build the next AI model, Teradyne supplies the sophisticated automated testing equipment and software that semiconductor manufacturers rely on to ensure increasingly complex AI chips actually work before they leave the factory.

Whether Nvidia Corp. (NVDA), Advanced Micro Devices Inc. (AMD), or another chipmaker wins the AI race, those chips still need to be tested. That’s exactly the kind of “Golden Rivets” business Eric likes to own.

These are the firms that will be fueling the big AI names. They will be building the chips… powering the data centers… and perhaps even running AI servers in space.

Teradyne is one of four semiconductor-related companies Eric discusses in his free Market Shock presentation. There, he explains why he believes AI’s next phase could reward these overlooked “Golden Rivets” businesses far more than today’s crowded AI trades—and reveals the other three stocks currently on his radar.

Every investor pays tuition eventually. The trick is paying a few hundred dollars… instead of a few billion. Hopefully, today’s lesson saves you from the latter.

If you’d like to see the rest of Eric’s “Golden Rivets” framework, I think you’ll get a great deal out of his free Market Shock presentation.

Regards,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

The post 4 AI Stocks Built to Outlast the Hype appeared first on InvestorPlace.

Imagine that you own a Formula One race car.

It has a 1,000-horsepower engine, a carbon-fiber body, and tires with so much grip that they can almost stick to the ceiling. You hire the world’s best driver and spend millions tuning every part for speed.

Then race day arrives… and there is no fuel.

You may own one of the finest machines ever built, but it’s a very expensive paperweight without fuel.

That is the blind spot hiding inside the Magnificent Seven’s AI boom.

Amazon.com Inc. (AMZN), Microsoft Corp. (MSFT), Alphabet Inc. (GOOG), Meta Platforms Inc. (META), Nvidia Corp. (NVDA), Apple Inc. (AAPL), and Tesla Inc. (TSLA). These are all remarkable companies that have built some of the top F1 vehicles of the AI Revolution.

• Data centers…
• Custom chips…
• Advanced AI models…

And they all suffer from the same blind spot: They don’t produce the “fuel” that allows their multibillion-dollar AI investments to run. Instead, this role is filled by chipmakers… electrical utilities… data center construction firms… and other behind-the-scenes producers making the essential ingredients for the AI Revolution.

InvestorPlace Senior Analyst Eric Fry calls these components “Golden Rivets.” And in his recent free broadcast, he reveals why they are creating a $10 trillion opportunity that is even better than the one offered by the Magnificent Seven.

Today, I’m going to reveal one of these Golden Rivets and three top picks that are churning it out. To find out the rest, you’ll have to watch Eric’s Market Shock presentation here.

One Golden Rivet of the AI Revolution

The Golden Rivet I’m going to discuss is everywhere in our modern lives. But you can’t touch or taste it… and you’re not supposed to see or hear it (unless something has gone very, very wrong).

I’m talking about electricity… one of the greatest bottlenecks of the AI Revolution. And over the next several years, we are going to hear a lot about this invisible force.

That’s because electricity is expected to be the No. 1 reason for data center project delays. Analysts currently forecast that around 40% of all planned data centers for 2026 will get pushed into 2027… and the cause will be either the lack of power equipment (transformers, battery systems) or the inability to connect data centers to the main electrical grid. That will push construction planned for 2027 into 2028… and so on.

In other words, the Magnificent Seven companies are building massive power-hungry data centers, but they have nowhere to plug them in.

That’s going to create a bonanza for power utilities and electrical component makers that supply AI data centers. In fact, some power companies have sold out their production through 2030. High-voltage transformers and heavy-duty gas turbines are now even harder to obtain than the highest-end Nvidia chips, simply because there are none available.

Now, here are three electricity Golden Rivet companies that should benefit, from the riskiest to the least risky…

The Moonshot Bet

You might recognize my first pick from a Sunday Digest last year when the company still traded in the $8 range:

Fluence Energy (FLNC).

Fluence is a utility-scale energy storage provider. Think of it as storing power in a bottle: Fluence charges massive arrays of batteries when too much electricity is generated, and then dumps it back into the grid when it is needed.

Demand for Fluence’s services has been incredible. Virtually every AI data center needs battery backup systems, because gas turbines cannot spin up fast enough to keep up with sudden demand spikes. Fluence’s batteries give that extra jolt. Ask any child who has ever licked a 9V cell.

The popularity of renewables like solar and wind power has further charged demand for Fluence’s products. After all, AI data centers still need power when the sun doesn’t shine and the wind doesn’t blow. Many energy grids even let data centers jump in line for grid connections if they have on-site batteries. Fluence’s revenues are expected to rise 48% this year, and then another 24% in fiscal 2027 – some of the fastest growth rates in the business.

Keep in mind that the share prices of this promising startup sometimes trade wildly. The stock rose as high as $33.50 in January – a 4X increase from my July 2025 recommendation – before plummeting 50% back into the low-teens range. Fluence will remain unprofitable until 2027, so its stock price will depend on investor mood. Earlier this week, the stock plummeted 26% in after-hours trading before opening back up to almost where it started.

But the same volatility is now giving investors a second chance to buy shares. The stock is now trading under $14, and its flip from negative profits to positive next year should act as the catalyst that buy-and-hold investors need to all pile in all at once.

The Cheapest Entry Point

A less volatile way to play the electricity Golden Rivet is Legrand SA (LGRDY), a French company that builds the electrical plumbing inside data centers.

This includes components like:

• Busways. Overhead power highways that feed AI servers
• Breakers. Heavy-duty protection against power surges
• Power distribution units. Complex power strips for individual servers
• Monitoring equipment. Measurement equipment to identify potential failures

In other words, Legrand moves electricity from a data center’s main power electrical room to each server and manages the things that can go wrong. Data centers now make up more than 32% of sales, up from 15% in 2023.

Legrand is one of the cheapest companies in the business because it primarily trades on the Euronext Paris, where it is valued like a European wiring company. Shares trade at just 22.5X forward earnings. That is far lower than Legrand’s American-traded peers, including Eaton Corp. Plc (ETN) at 30X and Rockwell Automation Inc. (ROK) at 31X. These U.S. firms actually have lower data center revenue shares.

In addition, Legrand has already raised its 2026 guidance twice and has acquired the capabilities it needs for a 2028 industry-wide switch to a new 800-volt standard. That should keep driving sales higher. And as for that whole “European wiring” caricature… roughly half of its sales now go to North America.

That means we should begin to see a convergence between this French company and its American peers. My base case is for a 30% return, and possibly higher if insatiable AI data center demand keeps pushing expected earnings higher from here.

The Quiet Compounder

Finally, the power industry’s bluest of blue-chip award goes to Constellation Energy Corp. (CEG), America’s largest producer of nuclear energy. The Baltimore-based firm operates roughly two dozen nuclear reactors, which generate enough power to supply 16 million typical American homes. It also has a large portfolio of wind, solar, natural gas, and hydroelectric plants, which can supply another 11 million homes.

Nuclear energy is a particularly excellent source of electricity for AI data centers. Reactors are very low-cost once they are built and provide the kind of cost stability that tech companies prize. Fuel makes up less than 20% of a nuclear power plant’s cost, compared to 65% to 80% for gas power plants.

Nuclear plants also produce electricity 24/7, giving them an advantage over solar and wind, which require the expensive batteries (often from Fluence) to properly run.

That’s made Constellation’s shares slightly more expensive than its peers, especially those that focus on gas power. CEG trades at 23X forward earnings, compared to a 19.7X sector average. Constellation also holds somewhat high debts because of a 2025 acquisition of another power producer, Calpine Corp.

However, the premium could be worth it for three key reasons:

Constellation’s stock should not rise as quickly as Fluence or Legrand. Its size and stability make fireworks less likely. Nevertheless, I still expect the stock to grind higher from around $265 to $320 in the next year or so, making it an appropriate bet for risk-averse investors.

The Other Golden Rivets of the AI Revolution

In late-2025, Microsoft CEO Satya Nadella revealed that his firm had AI chips sitting on shelves because the company didn’t have enough power to install them.

“You may actually have a bunch of chips sitting in inventory that I can’t plug in,” Nadella said in an online interview. “In fact, that is my problem today.”

This is Microsoft we’re talking about… a $3.7 trillion firm. And they couldn’t find enough electricity to run the chips they had bought.

It turns out Microsoft is not the only Mag 7 company suffering from AI bottlenecks. Nvidia has been forced to delay production of its highest-end chips because its suppliers couldn’t keep up. Apple has been forced to raise prices of iPhones from a “a hundred-year flood” of memory chip shortages. And Elon Musk’s xAI has turned to using dozens of gas turbines without permits to power its “Colossus” supercomputer in Memphis because Tesla’s “Megapack” systems can’t provide enough juice.

Everywhere you look, there are bottlenecks in the AI buildout.

That’s where Eric’s Golden Rivets come in. These are the firms producing these components in such short supply.

In his free Market Shock presentation, he’s revealing his top picks, including 15 free stocks, that he believes will profit from the growing AI shortages.

Click here to check it out.

Until next week,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post The Mag 7’s $10 Trillion Blind Spot… and 3 Stocks to Buy for It appeared first on InvestorPlace.

If you’d like to see the complete picture, Eric also expands on these ideas in his free Market Shock presentation, where he shares several additional stocks he believes deserve investors’ attention.

The universe wasn’t supposed to do this.

In 1998, astronomers made a discovery so surprising that it eventually earned three of them the Nobel Prize in Physics.

The expansion of the universe was accelerating.

That flew in the face of decades of scientific thinking.

Ever since Edwin Hubble discovered in 1929 that the universe was expanding, astronomers had assumed gravity would gradually slow that expansion over time. The only real question was how much it had slowed.

To find the answer, scientists turned to extraordinarily distant exploding stars known as supernovae. Because these stellar explosions have a predictable brightness, astronomers can use them as mile markers in space, comparing how bright they should appear with how bright they actually look from Earth.

What they discovered turned conventional wisdom on its head.

Those supernovae were fainter – and, therefore, farther away – than expected. Instead of slowing under gravity’s pull, the universe was expanding at an accelerating rate.

Something scientists couldn’t see or explain was pushing space outward.

Observations from the Hubble Space Telescope – named after Edwin Hubble himself – helped confirm the finding and deepen the mystery. Even today, the nearby universe appears to be expanding roughly 5% to 9% faster than our best models predict.

Now another space-related expansion appears to be accelerating, one with much more immediate consequences for investors.

The global space economy recently reached a record $613 billion. Johns Hopkins researchers expect it to approach $1.8 trillion within the next decade, fueled by reusable rockets, private investment, falling launch costs, and entirely new businesses that would have sounded like science fiction only a few years ago.

And now artificial intelligence is accelerating that expansion even further.

AI is already helping companies design spacecraft, process vast quantities of satellite data, automate missions, and explore the possibility of operating data centers in orbit. Space is no longer merely somewhere technology travels. It may become part of the infrastructure where tomorrow’s most advanced computing takes place.

That brings us to Space Exploration Technologies Corp. (SPCX).

SpaceX Earnings Reveal a New AI Bottleneck 

This week, investors received their first detailed look inside the newly public company. The results showed a business evolving far beyond rocket launches and satellite communications and spending staggering sums to become a major force in AI infrastructure.

SpaceX generated $7.8 billion in second-quarter revenue, up roughly 92% from a year earlier. But it also spent nearly $16 billion expanding its AI infrastructure, helping produce a quarterly net loss of $541 million.

Yet when Elon Musk discussed what could limit that expansion, he did not point to SpaceX’s losses, its access to capital, or even the availability of advanced AI chips.

“The limiting factor currently is memory,” Musk told investors.

For investors, that admission may prove far more valuable than anything else in SpaceX’s earnings report.

Because the memory shortage constraining Musk’s AI ambitions is also creating severe supply-and-demand imbalances throughout the technology industry. And the relatively small group of companies capable of supplying that memory could possess exactly what investors should look for during a shortage: surging demand, limited competition, rising prices, and extraordinary pricing power.

Today, I’ll show you why Elon Musk believes memory (not money) is becoming AI’s biggest constraint and how that shortage could reshape the industry.

Plus, I’ll introduce you to one memory company I believe is positioned to benefit… and show you where you can find three more memory-related stocks I’m watching before Wall Street fully catches on.

Why AI Memory Is SpaceX’s Biggest Infrastructure Bottleneck

When Elon Musk called memory “the limiting factor” for SpaceX’s AI ambitions, he wasn’t talking about some obscure engineering problem.

He was describing a challenge that now confronts virtually every company trying to build the next generation of artificial intelligence.

SpaceX wants to become much more than a launch company. Musk envisions it operating enormous AI data centers, processing data gathered by Starlink’s thousands of satellites, developing autonomous spacecraft, and ultimately creating an AI infrastructure business that extends well beyond Earth’s atmosphere.

But none of that can happen without memory.

Modern AI systems rely on three essential building blocks:

• GPUs, like Nvidia’s AI accelerators, which perform the calculations. 
• HBM (high-bandwidth memory), the ultrafast memory attached directly to those GPUs. 
• DRAM (dynamic random access memory), the working memory that allows AI models to “think” in real time. 

The first bottleneck of the AI boom was compute. Nvidia Corp. (NVDA) became one of the world’s most valuable companies by solving that problem.

That bottleneck has shifted. Now it’s memory.

Large language models don’t simply perform calculations. They must constantly store, retrieve, and manipulate staggering amounts of information while generating each response.

Training a ChatGPT-sized model can require tens or even hundreds of terabytes of DRAM spread across thousands of GPUs. Without enough memory, those expensive AI systems simply wait.

No memory means no intelligence.

That’s why Nvidia CEO Jensen Huang recently warned that the industry’s “memory bottleneck is severe.”

It’s also why tech companies have reportedly stationed employees in South Korea for months at a time, hoping to secure scarce DRAM allocations from Samsung and SK Hynix Inc. (SKHY). The industry has even given these buyers a nickname: “DRAM beggars.”

SpaceX may have been the first company to say it publicly, but it certainly won’t be the last.

PDF Solutions: A Picks-and-Shovels Play on the AI Memory Shortage

The numbers explain why. 

Nearly 100 gigawatts of new AI data centers are expected to come online over the next four years. Yet industry estimates suggest there is enough DRAM supply to support only about 15 gigawatts of new capacity over the next two years.

That imbalance is already driving prices sharply higher. Market researcher TrendForce expects conventional DRAM contract prices to surge 90% to 95% in early 2026, one of the fastest increases the industry has ever experienced.

During SpaceX’s earnings call, Musk added another eye-opening statistic. He expects AI memory demand to grow at nearly 200% annually.

That combination – exploding demand and constrained supply – is exactly the sort of bottleneck I like to look for as an investor.

One company I’ve got my eye on is PDF Solutions Inc. (PDFS).

Unlike memory manufacturers themselves, PDF Solutions helps semiconductor companies produce more usable chips from every manufacturing run. Its software identifies defects, improves manufacturing yields, and helps chipmakers reduce costly failures. Those are capabilities that become dramatically more valuable when every additional AI memory chip commands a premium.

As manufacturers race to increase DRAM and HBM production, companies like PDF Solutions quietly become indispensable behind the scenes.

That’s one reason PDFS has become one of the most interesting memory-related stocks I’m watching.

It isn’t the only one.

Where the Next AI Memory Winners May Emerge

If you’ve followed my work for any length of time, you know I spend very little time chasing whatever Wall Street already loves.

Instead, I look for the bottlenecks.

Years ago, that meant identifying Nvidia before most investors appreciated how valuable AI compute would become.

Last year, it meant recognizing that the AI trade was entering a new phase, one where the biggest gains would increasingly come from the companies supplying what I call AI’s Golden Rivets. Those are the irreplaceable materials, energy, networking, and memory infrastructure every AI company depends upon. 

Today, I believe we’re entering the next phase of that acceleration.

Much like the astronomers who assumed the universe’s expansion would gradually slow, I believe many investors are underestimating what’s happening today. They see AI continuing to grow, but they haven’t yet recognized how quickly demand for the infrastructure supporting that growth is accelerating.

And as we’ve already seen with SpaceX, those accelerating demands are beginning to expose entirely new bottlenecks… and entirely new investment opportunities.

In my Market Shock presentation, I explain that while the AI Revolution is still in its early innings, the next big winners are unlikely to be the same companies that dominated the last three years.

I’ll also share four memory-related stocks I believe are positioned to benefit from this bottleneck, including three additional names and tickers beyond PDF Solutions that I’m watching very closely.

If you’d like to see the complete framework, and why I believe SpaceX’s earnings call may have revealed far more than Wall Street realizes, you can watch that free presentation here.

The post The AI Memory Shortage Could Make These 4 Stocks Winners appeared first on InvestorPlace.

In a crossword puzzle, every answer connects. Solve one clue, and another piece suddenly falls into place.

Here’s one: Three words investors hate to see: “supply is ____”

Seven letters across. One answer.

Limited.

That word is becoming one of the most important clues in the AI investment puzzle.

The world wants more AI – more chips, more servers, more electricity, more data centers. But the supply of these critical resources is failing to keep up with demand.

And when supply runs short, the companies supplying the resources could emerge as the biggest winners. That’s why it’s essential for investors to consider the bottlenecks forming within the AI industry.

So, in today’s Smart Money, I’ll examine the two growing constraints of AI, how they may influence which companies will thrive, and the proper ways to invest in them.

Where AI Is Hitting Its Limits

Let’s start with what makes the AI Revolution go ’round: Energy. 

Data centers are filled with expensive chips from companies like Nvidia Corp. (NVDA) and Advanced Micro Devices Inc. (AMD). But those chips must be powered to do any work… otherwise they are just pricey doorstops.

In other words, power isn’t just important to AI growth. It is AI growth. And it has become one of AI’s biggest bottlenecks. 

Demand for power near data centers is already straining local grids. In some areas, electricity now costs up to 267% more than it did five years ago. That means the next AI winners may not just be the companies building smarter machines, but the companies supplying the energy needed to run them.

Meeting this demand will require an all-hands-on-deck approach. That means wind, solar, nuclear, and natural gas. Hyperscalers like Microsoft Corp. (MSFT), Alphabet Inc. (GOOGL), and Amazon.com Inc. (AMZN) are already investing in nuclear, natural gas, and other dedicated power sources to guarantee electricity for future AI infrastructure. For example…

• Microsoft signed a 20-year deal to buy electricity from the planned restart of Three Mile Island nuclear plant in Pennsylvania.
• Alphabet partnered with Kairos Power to develop electricity from small modular reactors (SMRs).
• Amazon is investing $20 billion in Pennsylvania AI data centers, including a campus near the Susquehanna nuclear plant to secure the power needed for AI.

Electricity is clearly becoming a competitive advantage. But it’s only one chokepoint. The next bottleneck is something every AI system needs to function…

What Every AI System Needs

It needs memory, also known as DRAM.

Without enough DRAM, AI systems simply run out of room to process information. And the shortage may persist for years. Nearly 100 gigawatts of new data centers are scheduled to come online over the next four years. But there’s only enough DRAM to support roughly 15 gigawatts over the next two years. 

Without memory, artificial intelligence literally can’t think. 

Nvidia CEO Jensen Huang put it plainly: “The memory bottleneck is severe.” 

And Elon Musk just announced in Space Exploration Technologies Corp.’s (SPCX) first earnings report this past week: “The limiting factor currently is memory.”

So, don’t just take it from me. Take it from the titans of the AI industry.

These bottlenecks are very real, and they will affect how the AI investing unfolds. But it is still missing a key piece; energy and memory are only two constraints.

The Bottleneck Blueprint

This isn’t the first time technology has created a shortage of essential resources. The same pattern appeared during the dot-com boom – when the internet’s rapid expansion created unexpected winners beyond the companies building the digital world.

The explosion of internet infrastructure, personal computers, and networking hardware meant the world suddenly needed far more metals than usual. I’m talking about copper… tantalum… germanium… and other essential ingredients to build the physical internet.

But mining and refining capacity couldn’t expand overnight. The result was a classic supply bottleneck. But investors who anticipated which resources would become scarce had the chance to profit in extraordinary ways.

From 1998 to 2001, I recommended four mining stocks to my readers that went on to generate remarkable gains. These companies became the quiet winners of the late-1990s tech boom.

One of them was Antofagasta plc (ANTO.L), which had become a copper-focused mining company.

I recommended Antofagasta to my readers on December 18, 1998 – about a year before the mine began production.

• Over the next three years, the stock soared 205%, while the S&P 500 was essentially flat.
• Over six years, Antofagasta delivered an astonishing 778% gain, while the S&P continued to nurse its losses, down 27%!

Antofagasta solved the puzzle before most investors even saw the clue. It built capacity during the investment phase of the 1990s – then benefited enormously once the metals bottleneck tightened.

That’s the power of identifying bottlenecks early. Now, we have the opportunity to apply this strategy again.

The Hidden Clues Behind AI’s Next Winners

The word limited is only the first clue in the AI investment puzzle. To find the biggest opportunities, investors need to solve four more:

If you want to know the answers to these questions, check out my free Market Shock presentation, where I dive even deeper into AI’s physical limitations: energy, memory, and the third bottleneck that could shape the next wave of AI winners.

I also reveal the types of companies that could benefit most from these constraints, including 15 free stocks – ticker symbols and all – that I believe are positioned to profit from the AI shortage problem.

Understanding AI’s power is essential when choosing stocks for your portfolio. But every great puzzle has hidden clues. By identifying the bottlenecks holding AI back, investors can uncover the companies positioned to benefit most from solving them.

Click here to learn how.

Regards,

Eric Fry

The post AI’s Biggest Bottlenecks Could Create Its Biggest Opportunities appeared first on InvestorPlace.

It’s a Hollywood story that reads more like fiction.

It’s about a billionaire who got rich from the movies in a most unusual way.

He never starred in a movie. Never directed one. Never wrote a screenplay, ran a production studio, or produced a single motion picture.

But he changed the industry forever by inventing a technology to make every movie better.

You almost certainly know Ray Dolby’s last name, but you probably don’t know his story.

In the 1960s, recorded sound had a problem. The tape used for film audio recordings produced an annoying background hiss that studios struggled to eliminate.

Dolby, an electrical engineer and physicist, developed a technology that dramatically reduced that noise. But then he turned his attention to movie theaters.

His company helped introduce the immersive surround sound that made audiences feel as if an explosion, spaceship, or speeding car had passed directly through the theater.

Dolby Surround Sound transformed moviemaking.

Credit: Eva Gattuso

Ten years after its introduction, approximately 6,000 theaters worldwide had installed the technology.

Ray Dolby wasn’t a filmmaker. But the people who did make them needed what his company supplied.

That made Dolby a billionaire. It also made his name so closely associated with movies that the theater that hosts the Academy Awards is now called the Dolby Theatre.

It’s a valuable reminder:

You don’t always have to create the finished product to profit from its success.

Sometimes, the better opportunity is supplying one indispensable piece that the finished product cannot exist without.

That may be especially important as Elon Musk prepares for what could be his most ambitious undertaking yet.

The AI Supplier Pipeline

Regular Digest readers know that our technology investing expert, Luke Lango, is still bullish on everything AI. But that doesn’t mean just investing in the big names everyone already knows.

In an April issue of Innovation Investor, Luke recommended a smaller company that provides a critical part of the infrastructure needed to make AI happen.

It’s important to remember that even technology megatrends sometimes need physical work done – work that involves heavy machinery and guys with hard hats. That’s why Luke recommended Dycom Industries (DY).

Here is Luke describing why DY is a critical part of the AI story.

Dycom is the dominant player in the design, installation, and maintenance of telecommunications infrastructure across the United States. When AT&T decides it needs to densify its fiber network in the Southeast, it calls Dycom. When Verizon needs to extend fiber-to-the-home buildout in the mid-Atlantic, it calls Dycom. When a hyperscaler needs dedicated fiber routes between data center campuses, it calls Dycom. 

The AI connection is direct and mathematically unavoidable. Every ChatGPT query traverses physical fiber. Every AI-generated image, every real-time language model inference call, every agentic AI workflow that executes a multi-step task — all of it requires low-latency, high-bandwidth connectivity between data centers, edge compute nodes, and end users. 

DY is a perfect illustration of a company most people don’t know, yet it remains critical to the ambitions of the AI hyperscalers we all know.

The stock was caught in the same meltdown as other AI stocks in July, but since Luke’s April recommendation, it has risen about 12%.

As I write, DY trades around $400, well below Luke’s $500 buy-below price, so there is plenty of room to establish a position in this pick.

Now, Luke has identified three more under-the-radar suppliers that could provide the infrastructure, equipment, and materials for Elon Musk’s most ambitious project yet.

Elon’s Next Big Project

This opportunity could be much bigger than anything else we’ve seen in the AI megatrend.

Luke believes Musk is preparing to unite the capabilities of Tesla (TSLA), SpaceX (SPCX), xAI, and X around a single sweeping vision.

Part of that vision includes building enormous AI data centers in space… constructing a 100-million-square-foot semiconductor complex in Texas… and deploying armies of Optimus robots to automate much of the work.

It’s an ambitious project that seems to dwarf everything Musk has done so far.

Even attempting all these projects would require extraordinary amounts of specialized aerospace hardware, semiconductor-manufacturing equipment, rare earth elements, and powerful permanent magnets.

Musk’s companies cannot immediately produce all those components themselves.

They will need suppliers.

And much like Ray Dolby’s company, some of those suppliers could become enormously valuable without ever receiving top billing.

That’s where Luke is looking.

In a new presentation, he reveals three companies he believes could become indispensable to Musk’s plans. Most investors have probably never heard of these companies, but that is precisely the point.   

By the time a supplier’s name appears in the headlines alongside Tesla or SpaceX, much of the opportunity may already be priced into its shares.

Luke wants to help you learn their names before that happens.

That’s why he recently recorded a special presentation explaining Musk’s plan, the enormous supplier pipeline it could create, and the three little-known companies he believes are best positioned to benefit.

Dycom’s recent rise shows why it can pay to look beyond the famous company receiving all the headline attention and identify the specialists supplying the technology it cannot operate without.

Ray Dolby never made a movie. He simply provided the sound that every great movie needs.

Luke believes these three companies could occupy a similar position in Elon Musk’s next blockbuster.

Click here to watch Luke’s presentation and discover the three companies that could help build Elon Musk’s next technological empire.

Enjoy your weekend,

Luis Hernandez

Editor in Chief, InvestorPlace

The post A Billion Dollar Lesson for Investors appeared first on InvestorPlace.

Take Long-Term Capital Management (LTCM).

The hedge fund was run by some of the smartest minds in finance, including two Nobel Prize-winning economists. It used sophisticated mathematical models to exploit tiny pricing discrepancies in global bond markets.

For years, the strategy worked.

Then Russia defaulted on its debt in 1998. Markets moved in ways LTCM’s models had not anticipated, and the fund’s enormous leverage turned mounting losses into a crisis. It came so close to collapsing that the Federal Reserve helped organize a Wall Street rescue.

Then there was Archegos Capital Management in 2021.

Founder Bill Hwang built huge positions in a handful of stocks using borrowed money and derivatives. But there was more going on than aggressive investing. Hwang and his team lied to Wall Street banks about the size and concentration of Archegos’s portfolio and manipulated the prices of stocks it owned.

When those stocks started falling, Archegos faced massive margin calls it could not meet. Banks unloaded tens of billions of dollars in stock, and the firm imploded within days. Hwang was later convicted of fraud.

Now we have another spectacular hedge-fund blowup to add to the list.

This one involves Situational Awareness, an AI-focused hedge fund run by a 24-year-old former OpenAI researcher named Leopold Aschenbrenner.

And to be clear, there is no indication that Aschenbrenner did anything fraudulent.

His mistake appears to have been much simpler.

He got very smart about artificial intelligence, made a fortune betting on it and then used enough leverage that the market eventually took control of his portfolio away from him.

For a while, it looked brilliant.

Situational Awareness reportedly soared 439% in the first half of 2026.

Then July arrived – and one of the smartest young minds in AI got pummeled by the market.

Folks, there’s an important lesson here.

Being smart can give you an edge in the market. But believing you’re smart enough to outwit the market can get very expensive, very quickly.

And I think that lesson is especially important for AI investors right now.

Because after three years of enormous gains, the AI landscape is starting to change. The companies and technologies that led the first stage of this boom will not necessarily lead the next one.

In today’s Market 360, we’ll take a closer look at how Situational Awareness went from one of the hottest hedge funds on Wall Street to a forced liquidation in a matter of weeks. Then I’ll explain why its collapse offers a timely warning for AI investors as we approach what I believe could be the next major reset in the artificial intelligence market.

The “Nostradamus of AI”

Now, Aschenbrenner wasn’t some amateur who wandered into the AI trade at the top.

He entered Columbia at 15, graduated as valedictorian at 19 and later worked for the FTX-linked Future Fund before joining OpenAI. He was eventually fired from OpenAI after a dispute over the company’s information security practices.

His reputation really took off after he published an essay in 2024 called Situational Awareness. It laid out an aggressive vision for AI and the enormous amounts of chips, memory, electricity and data-center infrastructure it would require.

Then he put real money behind that thesis.

Aschenbrenner launched a hedge fund under the same name. The early results were extraordinary.

MarketWatch reported that Situational Awareness had gained more than 2,000% since its September 2024 launch. The fund was up roughly439% in the first half of 2026 alone.

Assets under management reached as much as $45 billion by early July.

At 24 years old, Aschenbrenner looked like a genius.

In fact, when the week began, he was preparing for a multiday wedding celebration in Carmel. By the time guests started arriving, his fund was unraveling and the vultures were circling.

Then the market turned.

When Leverage Takes Over

July was already shaping up to be a rough month for AI and data-center stocks.

The first wave hit when mean-reversion algorithms began attacking some of the market’s strongest momentum stocks. AI and data-center names were hit especially hard.

Then came another scare on July 17. Chinese AI startup Moonshot released a new large language model called Kimi K3, claiming it could rival leading Western models at a fraction of the cost.

Short sellers quickly seized on the news and started calling it a “DeepSeek 2.0 moment.” The argument was familiar: If Chinese companies could build cheaper AI models, perhaps the U.S. would not need as many expensive chips, data centers and power projects after all.

That narrative hit AI infrastructure stocks hard and pushed the NASDAQ close to correction territory.

Then DeepSeek added more pressure late in the month by releasing a new model at a fraction of the price charged by U.S. competitors.

OpenAI responded by cutting the price of one of its models, while Google rolled out new efficiency-focused offerings.

That sparked talk of an AI price war.

And unlike some of the rumors short sellers like to spread, there may be something behind this concern.

AI model costs are falling quickly. But I’ve consistently pointed out that cheaper AI does not necessarily mean less AI.

Lower costs can drive a lot more usage. And all that additional AI activity still requires chips, memory, electricity and data centers.

Unfortunately for Situational Awareness, that distinction didn’t matter in the middle of a bloody selloff.

The fund was heavily concentrated in many of the AI and data-center stocks already under pressure. And according to media reports, at times it was leveraged by up to four times its underlying capital.

As those stocks kept falling, prime brokers reportedly began demanding that Situational Awareness reduce risk. That forced the fund to sell into an already weak market, adding even more pressure to the same stocks it owned.

By the end of July, The Wall Street Journal reported that Situational Awareness had plunged 67% for the month. The fund eventually sold the bulk of its leveraged public-stock portfolio to Citadel in a massive block trade.

That appears to have been the final capitulation event.

And it is also where this story gets especially interesting for us…

Why Capitulation Is Good News…

What I find fascinating is that seven companies disclosed in Situational Awareness’s latest 13F also appear in our current Growth Investor portfolio.

Seven.

That includes names like Bloom Energy Corporation (BE), Micron Technology, Inc. (MU) and NVIDIA Corporation (NVDA).

So, I’m certainly not going to criticize Aschenbrenner for recognizing good AI opportunities. In several cases, we identified the exact same companies.

We first bought NVIDIA in May 2019. As of right now, we were sitting on a gain of 5,245%.

We added Bloom Energy in September 2025, and it is up about 212%.

And Micron, which we added at the end of January, had nearly doubled in about six months, giving us a gain of roughly 112%.

The difference wasn’t the stocks.

The difference was that we didn’t get greedy.

Situational Awareness used borrowed money to magnify its bets. That produced spectacular returns on the way up, but it also meant Aschenbrenner could not simply wait when the market temporarily moved against him.

His lenders eventually forced his hand. Meanwhile, over at Growth Investor, all we had to do was wait out the storm.

And what happened next helps explain why I believe the worst of July’s correction may be behind us.

For days, Wall Street had suspected that Situational Awareness was contributing to the relentless selling in AI stocks. Once news broke that Citadel had absorbed much of its public-equity portfolio, traders suddenly knew that a major forced seller was now out of the market.

Buyers rushed back in.

Bloom Energy surged about 26% the next day. Sandisk Corporation (SNDK) jumped roughly 26%. Several other recent Situational Awareness holdings posted huge one-day gains, too.

What that tells me is that Situational Awareness was dumping stock because it had to. Once that liquidation ran its course, buyers were willing to step back in.

That’s what we call capitulation, folks.

Don’t Outsmart the Market

There is a simple lesson in all of this.

Aschenbrenner knew AI. He identified several major winners. And for a while, he made an extraordinary amount of money.

Frankly, I wouldn’t be surprised if we hear from Aschenbrenner again. He’s only 24 years old, he clearly understands AI, and several of his stock ideas were very good. He just learned an extraordinarily expensive lesson.

But even the smartest investor can get pummeled by trying to outsmart the market.

That’s worth remembering now because AI is entering another major transition.

I remain extremely bullish on AI. But I don’t expect the companies and technologies that dominated the first phase of this boom to automatically dominate the next one.

My research team and I have spent months studying a massive new effort taking shape across America’s national laboratories.

President Trump has compared it to a new Manhattan Project for AI. At its center is a new network of government supercomputers and AI infrastructure that I call Golden Dawn.

The goal is to use AI to accelerate scientific breakthroughs in areas ranging from energy and medicine to advanced materials and quantum computing. And I believe the companies helping build that infrastructure could represent the next major group of AI winners.

That’s why I recently put together a special presentation called The AI Reset of 2026.

In it, I explain what Golden Dawn is, reveal the stocks I believe are positioned to profit from it and identify several well-known stocks I think investors should approach with caution.

Click here to watch my full AI Reset of 2026 presentation and see how I’m preparing for what comes next.

Sincerely,

Louis Navellier

Editor, Market 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

Bloom Energy Corporation (BE), Micron Technology, Inc. (MU), NVIDIA Corporation (NVDA) and Sandisk Corporation (SNDK)

The post Lessons From the AI Genius Who Tried to Outsmart the Market appeared first on InvestorPlace.

Does bad luck actually exist?

Physicists have spent a century attempting to get to the bottom of this question. At the subatomic level, the universe looks like pure chaos. You cannot predict when a single atom will decay. But hand that same physicist a sample of those atoms, though, and he will tell you exactly how long it takes for half of them to fall apart. The individual event looks random but the ensemble is not. And a growing camp of physicists argues the randomness was never really there at all – that particles obey probabilistic rules, and probabilistic rules are deterministic rules wearing a disguise.

Remove one convenient assumption from the math and what looked like chance turns back into cause and effect.

Which brings us to July…

If you owned AI infrastructure stocks last month, it felt like the worst luck imaginable. The first half of 2026 felt like the best of times. From Jan. 1 to about June 22, we were invincible. We were Superman with Lois Lane in our arms. Then, from June 23 into July 30, it felt like the worst of times. Shout out Charles Dickens. Semiconductor stocks put in the deepest drawdown since ChatGPT launched, excluding the Liberation Day anomaly. The VanEck Semiconductor ETF (SMH) fell roughly 25%. The iShares Semiconductor ETF (SOXX) fell closer to 30%. Individual names got cut in half.

And every headline told you the same story: the AI trade is falling apart.

Here is the thing. That selloff was not random. It had a cause, a name, and a leverage ratio. And once you understand the mechanics, you stop seeing bad luck and start seeing one of the three best entry points of this entire AI cycle.

We discuss this (and more) in our latest episode of Being Exponential with Luke Lango below:

The Leopold Low

Situational Awareness was a large hedge fund built on one premise: AI compute is structurally undersupplied and stays undersupplied for years. Founded by Leopold Aschenbrenner, a genuine prodigy – Columbia at 15, valedictorian at 19, a stint at FTX, then a top research seat at OpenAI before an ugly exit over leaked documents.

He was directionally right. The fund loaded up on the neoclouds, the power names, the memory names, the optics names. It ripped, reportedly surging thousands of percent.

Then optimism turned into greed, and belief turned into overconfidence. Aschenbrenner levered up, reportedly at least four to one.

Now, everyone on the Street knew this. Everyone knew Leopold as the super-levered AI fund. So when the AI trade started to crack in late June, put yourself in the seat of a rival portfolio manager who owns a lot of the same names. You look at his book, you look at his leverage, and you think: if this guy blows up, he liquidates into my positions and takes my marks down with him. So what do you do? You sell everything you have in common with him first. You let him blow up. Then you buy it back cheaper.

That is exactly what the flow data from Goldman Sachs Group Inc. (GS) and Bank of America Corp. (BAC) showed in late June and July – institutional selling in tech at genuinely extreme levels, with no obvious fundamental trigger. It was not a verdict on the AI trade. It was a fire drill ahead of a fire everybody could see coming.

The fire arrived. Situational Awareness reportedly dropped about 67% month to date in July, and the public equity book got offloaded to Citadel through the prime brokers.

That was the clearing event. Leverage gone. Book in strong hands. No liquidation left to fear. The news hit on a Wednesday. Thursday was the big bounce. We have been bouncing ever since, and those same funds that sold in July are now enormous net buyers of tech.

Not luck. Mechanics.

Intelligence Is Not Wisdom

When you own stocks without leverage, you only have to be directionally correct. Add leverage, and you introduce a timing requirement. Now you have to be right about direction and right about when. You lose the ability to absorb a hiccup.

Aschenbrenner had extraordinary intelligence, which is the ability to see what is true. He did not yet have wisdom, which is the preparation for being right too early. That is a completely normal thing to lack at 25, in your first turn managing outside money. Bill Hwang and Archegos learned it in 2021. Long-Term Capital Management learned it in 1998. Ken Griffin blew up early too, and it made him what he is. Leopold will be back, and he will be better.

No cabal. No conspiracy. Just a levered book meeting a bad month.

Yes, We Are in a Bubble. That Is Not the Question.

I get asked constantly about concentration, and I will give you the honest answer: the market is heavily concentrated, and yes, we are in a bubble. Everything about this is consistent with a bubble.

I do not care that there is a bubble. I care when it bursts. Telling me the market is concentrated gives me nothing actionable. Timing is the entire game.

And we have been consistent about the timing tell for two years now: this bust happens when the hyperscalers stop spending.

They are not stopping. Amazon.com Inc. (AMZN), Microsoft Corp. (MSFT), Meta Platforms Inc. (META), and Alphabet Inc. (GOOGL) all reported over the last two weeks. All four posted excellent numbers. All four raised capex guidance for 2026. All four gave directionally bullish commentary on 2027, and implied continued spending into 2028. Alphabet is seeing rising Google Search usage and better ad effectiveness because of AI. Meta is growing daily active people on an already ubiquitous platform. Amazon Web Services and Azure both carry enormous backlogs.

Run the return math on those AI investments and you get a two-year return on invested capital in the high 20s. Weighted average cost of capital for these companies sits around 8% to 10%, which puts the two-year hurdle at roughly 16% to 20%. They are clearing it with room to spare. That is why the spending accelerates rather than slows.

Think of it as a funnel. Hyperscaler capex is water poured in at the top. Every AI infrastructure stock you own sits downstream, catching what flows through. We just got confirmation from all four pourers that they keep pouring. So stay invested in the recipients.

The Numbers Never Budged

Here is the chart that settles it for me, and it is the same chart I keep coming back to:

Stock price trends follow earnings estimate trends. The stock is not the company, and the company is not the stock, as Jeff Bezos put it in the wreckage of 2001. But the forward earnings estimate line tells you the underlying fundamental health of a business. When price detaches too far from that line, you get a buying opportunity.

Since June 23, forward earnings estimates for the Philadelphia Semiconductor Index have climbed roughly 10%. Over that same stretch, the index fell about 20%.

One of those two things has to give. Either estimates come down, or the stocks come back up. And estimates are not coming down, because the earnings are extraordinary and the capex funding them is rising.

That is what a fundamentally incongruent selloff looks like. That is why I have been telling subscribers this is backup-the-truck territory.

I will flag the honest counterargument, because it deserves one. In the 2022 tech wreck, price led fundamentals. Semiconductor stocks crashed while estimates kept rising, and then estimates rolled over and validated the crash. That is precisely what the market feared in July, and it is why beat-and-raise quarters were greeted with a shrug. The difference this time is that we heard directly from the companies funding the estimate line, and they told us they are spending more.

Where the Rebound Lands

Semis. Semis, semis, and then a little more semis.

Semiconductor stocks were the heartbeat of this market for three years. They took the worst of the July damage, which means they get the biggest snapback, and they are where the earnings growth actually is. Both SMH and SOXX have already retaken the 100-day moving average and broken the pattern of lower highs and lower lows. Oversold bounce, confirmed by the tape.

Underneath that, the individual Leopold Low names are the highest-torque way to play it. Bloom Energy Corp. (BE) put in a drawdown of roughly 50% while its forward estimate line went straight up and to the right, and it just reclaimed its 200-day. SanDisk Corp. (SNDK) fell about 56%, held the 200-day, knifed back through the 100-day, and took out its July lows to the upside.

On memory, I want to address the efficiency bear case directly, because it keeps coming up. Yes, the open-source models out of China are memory efficient. Yes, we get an efficiency breakthrough every few months. That is what new technology does. And every one of those breakthroughs triggers Jevons paradox – make a resource cheaper, and total consumption of it explodes. Efficiency gains are bullish for memory, not bearish.

Among the neoclouds, I recommend Nebius Group N.V. (NBIS) first and Applied Digital Corp. (APLD) second. APLD’s estimate line staged a sharp rebound that is completely incongruent with what the stock did. CoreWeave Inc. (CRWV) has the fundamental story right – we are compute short, and more supply is coming – but the chart has been stuck in neutral since the IPO, still below a flat 200-day. Good company. Better entries elsewhere.

One Thing to Watch

July also brought a broadening. The equal-weight index outperformed, and capital rotated into staples, discretionary, and software. A lot of people read that as a durable regime change.

I think it gets cut short. Capital is finite, and as the long end of the yield curve rises, it gets more finite. There is not enough of it to reconcentrate into AI infrastructure and broaden out simultaneously. So my rule of thumb: the dynamics that ruled from January to June are the dynamics to invest for. The dynamics of July are the ones to fade. What worked last month probably does not work from August to December, and what got crushed last month probably leads.

The universe may not deal in randomness. Neither does this market. Both just deal in causes most people never bother to trace.

For the full breakdown – the charts, the estimate divergences, and the complete list of Leopold Low names we are watching – listen to this week’s episode of Being Exponential.

In addition to the stocks I mentioned today, there is one $15 stock that could soar over the coming weeks and months. Hint: It involves Elon Musk, AI, China… 

There will be a headline that spooks you. Similar stocks that drop for reasons that have nothing to do with the business underneath it. A moment where it looks, on the surface, like the story is falling apart.

That moment, if history is any guide, is exactly when the money that matters moves in.

The only question left is whether you’re positioned before that moment or after it. In fact, if you buy just one stock for the rest of the year, I urge you to make it this one.

The post The Best Stocks to Buy on the Bounce After the ‘Leopold Low’ appeared first on InvestorPlace.

Our macro investment expert Eric Fry thinks the next chapter is about memory.

In today’s Friday Digest takeover, Eric explains why comments from SpaceX’s first earnings call may have revealed one of the AI boom’s biggest emerging bottlenecks – and why the companies helping solve that problem could be among the next generation of winners. He also highlights one stock already benefiting from this trend and explains why he believes Wall Street is still underestimating the opportunity.

If you’d like to dig deeper, Eric expands on this idea in his free Market Shock presentation, where he outlines his full “AI Golden Rivets” thesis and shares several additional stocks he believes are well positioned for AI’s next phase. You can watch it right here.

The biggest investment opportunities often emerge when the market realizes it has been focused on the wrong bottleneck. Eric makes a compelling case that we’re approaching one of those moments.

I’ll let him take it from here.

Have a good evening,

Jeff Remsburg

Hello, Reader.

The universe wasn’t supposed to do this.

In 1998, astronomers made a discovery so surprising that it eventually earned three of them the Nobel Prize in Physics.

The expansion of the universe was accelerating.

That flew in the face of decades of scientific thinking.

Ever since Edwin Hubble discovered in 1929 that the universe was expanding, astronomers had assumed gravity would gradually slow that expansion over time. The only real question was how much it had slowed.

To find the answer, scientists turned to extraordinarily distant exploding stars known as supernovae. Because these stellar explosions have a predictable brightness, astronomers can use them as mile markers in space, comparing how bright they should appear with how bright they actually look from Earth.

What they discovered turned conventional wisdom on its head.

Those supernovae were fainter – and, therefore, farther away – than expected. Instead of slowing under gravity’s pull, the universe was expanding at an accelerating rate.

Something scientists couldn’t see or explain was pushing space outward.

Observations from the Hubble Space Telescope – named after Edwin Hubble himself – helped confirm the finding and deepen the mystery. Even today, the nearby universe appears to be expanding roughly 5% to 9% faster than our best models predict.

Now another space-related expansion appears to be accelerating, one with much more immediate consequences for investors.

The global space economy recently reached a record $613 billion. Johns Hopkins researchers expect it to approach $1.8 trillion within the next decade, fueled by reusable rockets, private investment, falling launch costs, and entirely new businesses that would have sounded like science fiction only a few years ago.

And now artificial intelligence is accelerating that expansion even further.

AI is already helping companies design spacecraft, process vast quantities of satellite data, automate missions, and explore the possibility of operating data centers in orbit. Space is no longer merely somewhere technology travels. It may become part of the infrastructure where tomorrow’s most advanced computing takes place.

That brings us to Space Exploration Technologies Corp. (SPCX).

This week, investors received their first detailed look inside the newly public company. The results showed a business evolving far beyond rocket launches and satellite communications and spending staggering sums to become a major force in AI infrastructure.

SpaceX generated $7.8 billion in second-quarter revenue, up roughly 92% from a year earlier. But it also spent nearly $16 billion expanding its AI infrastructure, helping produce a quarterly net loss of $541 million.

Yet when Elon Musk discussed what could limit that expansion, he did not point to SpaceX’s losses, its access to capital, or even the availability of advanced AI chips.

“The limiting factor currently is memory,” Musk told investors.

For investors, that admission may prove far more valuable than anything else in SpaceX’s earnings report.

Because the memory shortage constraining Musk’s AI ambitions is also creating severe supply-and-demand imbalances throughout the technology industry. And the relatively small group of companies capable of supplying that memory could possess exactly what investors should look for during a shortage: surging demand, limited competition, rising prices, and extraordinary pricing power.

Today, I’ll show you why Elon Musk believes memory (not money) is becoming AI’s biggest constraint and how that shortage could reshape the industry.

Plus, I’ll introduce you to one memory company I believe is positioned to benefit… and show you where you can find three more memory-related stocks I’m watching before Wall Street fully catches on.

The Final Frontier’s Biggest Bottleneck

When Elon Musk called memory “the limiting factor” for SpaceX’s AI ambitions, he wasn’t talking about some obscure engineering problem.

He was describing a challenge that now confronts virtually every company trying to build the next generation of artificial intelligence.

SpaceX wants to become much more than a launch company. Musk envisions it operating enormous AI data centers, processing data gathered by Starlink’s thousands of satellites, developing autonomous spacecraft, and ultimately creating an AI infrastructure business that extends well beyond Earth’s atmosphere.

But none of that can happen without memory.

Modern AI systems rely on three essential building blocks:

• GPUs, like Nvidia’s AI accelerators, which perform the calculations.
• HBM (high-bandwidth memory), the ultrafast memory attached directly to those GPUs.
• DRAM (dynamic random access memory), the working memory that allows AI models to “think” in real time.

The first bottleneck of the AI boom was compute. Nvidia Corp. (NVDA) became one of the world’s most valuable companies by solving that problem.

That bottleneck has shifted. Now it’s memory.

Large language models don’t simply perform calculations. They must constantly store, retrieve, and manipulate staggering amounts of information while generating each response.

Training a ChatGPT-sized model can require tens or even hundreds of terabytes of DRAM spread across thousands of GPUs. Without enough memory, those expensive AI systems simply wait.

No memory means no intelligence.

That’s why Nvidia CEO Jensen Huang recently warned that the industry’s “memory bottleneck is severe.”

It’s also why tech companies have reportedly stationed employees in South Korea for months at a time, hoping to secure scarce DRAM allocations from Samsung and SK Hynix Inc. (SKHY). The industry has even given these buyers a nickname: “DRAM beggars.”

SpaceX may have been the first company to say it publicly, but it certainly won’t be the last.

One of the Companies Solving the Memory Problem

The numbers explain why.

Nearly 100 gigawatts of new AI data centers are expected to come online over the next four years. Yet industry estimates suggest there is enough DRAM supply to support only about 15 gigawatts of new capacity over the next two years.

That imbalance is already driving prices sharply higher. Market researcher TrendForce expects conventional DRAM contract prices to surge 90% to 95% in early 2026, one of the fastest increases the industry has ever experienced.

During SpaceX’s earnings call, Musk added another eye-opening statistic. He expects AI memory demand to grow at nearly 200% annually.

That combination – exploding demand and constrained supply – is exactly the sort of bottleneck I like to look for as an investor.

One company I’ve got my eye on is PDF Solutions Inc. (PDFS).

Unlike memory manufacturers themselves, PDF Solutions helps semiconductor companies produce more usable chips from every manufacturing run. Its software identifies defects, improves manufacturing yields, and helps chipmakers reduce costly failures. Those are capabilities that become dramatically more valuable when every additional AI memory chip commands a premium.

As manufacturers race to increase DRAM and HBM production, companies like PDF Solutions quietly become indispensable behind the scenes.

That’s one reason PDFS has become one of the most interesting memory-related stocks I’m watching.

It isn’t the only one.

Where I Think the Next Winners Will Come From

If you’ve followed my work for any length of time, you know I spend very little time chasing whatever Wall Street already loves.

Instead, I look for the bottlenecks.

Years ago, that meant identifying Nvidia before most investors appreciated how valuable AI compute would become.

Last year, it meant recognizing that the AI trade was entering a new phase, one where the biggest gains would increasingly come from the companies supplying what I call AI’s Golden Rivets. Those are the irreplaceable materials, energy, networking, and memory infrastructure every AI company depends upon.

Today, I believe we’re entering the next phase of that acceleration.

Much like the astronomers who assumed the universe’s expansion would gradually slow, I believe many investors are underestimating what’s happening today. They see AI continuing to grow, but they haven’t yet recognized how quickly demand for the infrastructure supporting that growth is accelerating.

And as we’ve already seen with SpaceX, those accelerating demands are beginning to expose entirely new bottlenecks… and entirely new investment opportunities.

In my latest Market Shock presentation, I explain that while the AI Revolution is still in its early innings, the next big winners are unlikely to be the same companies that dominated the last three years.

I’ll also share four memory-related stocks I believe are positioned to benefit from this bottleneck, including three additional names and tickers beyond PDF Solutions that I’m watching very closely.

If you’d like to see the complete framework, and why I believe SpaceX’s earnings call may have revealed far more than Wall Street realizes, you can watch that free presentation here.

Regards,

Eric Fry

Editor, The Speculator

P.S. Eric Fry has spent decades identifying major market shifts before they become obvious. His latest research suggests the next big winners won’t be the companies dominating today’s AI headlines, but the businesses supplying the critical infrastructure the entire industry depends on. If you enjoyed today’s essay, I think you’ll find his free Market Shock presentation well worth your time. In it, Eric explains his full thesis and shares several additional stocks he believes are positioned to benefit from AI’s next phase. Find it here.

The post SpaceX’s AI Bottleneck Could Mean Bigger Gains Ahead appeared first on InvestorPlace.

As Eric puts it, there’s one thing Elon Musk simply can’t spend his way around. And that single constraint could become one of the most profitable investment themes of AI’s next chapter.

Eric will explain more in the essay below. But if you’d like the full picture, you’ll want to check out Eric’s latest free Market Shock presentation.

Take it away, Eric…

*****************

Hello, Reader.

The universe wasn’t supposed to do this.

In 1998, astronomers made a discovery so surprising that it eventually earned three of them the Nobel Prize in Physics.

The expansion of the universe was accelerating.

That flew in the face of decades of scientific thinking.

Ever since Edwin Hubble discovered in 1929 that the universe was expanding, astronomers had assumed gravity would gradually slow that expansion over time. The only real question was how much it had slowed.

To find the answer, scientists turned to extraordinarily distant exploding stars known as supernovae. Because these stellar explosions have a predictable brightness, astronomers can use them as mile markers in space, comparing how bright they should appear with how bright they actually look from Earth.

What they discovered turned conventional wisdom on its head.

Those supernovae were fainter – and, therefore, farther away – than expected. Instead of slowing under gravity’s pull, the universe was expanding at an accelerating rate.

Something scientists couldn’t see or explain was pushing space outward.

Observations from the Hubble Space Telescope – named after Edwin Hubble himself – helped confirm the finding and deepen the mystery. Even today, the nearby universe appears to be expanding roughly 5% to 9% faster than our best models predict.

Now another space-related expansion appears to be accelerating, one with much more immediate consequences for investors.

The global space economy recently reached a record $613 billion. Johns Hopkins researchers expect it to approach $1.8 trillion within the next decade, fueled by reusable rockets, private investment, falling launch costs, and entirely new businesses that would have sounded like science fiction only a few years ago.

And now artificial intelligence is accelerating that expansion even further.

AI is already helping companies design spacecraft, process vast quantities of satellite data, automate missions, and explore the possibility of operating data centers in orbit. Space is no longer merely somewhere technology travels. It may become part of the infrastructure where tomorrow’s most advanced computing takes place.

That brings us to Space Exploration Technologies Corp. (SPCX).

This week, investors received their first detailed look inside the newly public company. The results showed a business evolving far beyond rocket launches and satellite communications and spending staggering sums to become a major force in AI infrastructure.

SpaceX generated $7.8 billion in second-quarter revenue, up roughly 92% from a year earlier. But it also spent nearly $16 billion expanding its AI infrastructure, helping produce a quarterly net loss of $541 million.

Yet when Elon Musk discussed what could limit that expansion, he did not point to SpaceX’s losses, its access to capital, or even the availability of advanced AI chips.

“The limiting factor currently is memory,” Musk told investors.

For investors, that admission may prove far more valuable than anything else in SpaceX’s earnings report.

Because the memory shortage constraining Musk’s AI ambitions is also creating severe supply-and-demand imbalances throughout the technology industry. And the relatively small group of companies capable of supplying that memory could possess exactly what investors should look for during a shortage: surging demand, limited competition, rising prices, and extraordinary pricing power.

Today, I’ll show you why Elon Musk believes memory (not money) is becoming AI’s biggest constraint and how that shortage could reshape the industry.

Plus, I’ll introduce you to one memory company I believe is positioned to benefit… and show you where you can find three more memory-related stocks I’m watching before Wall Street fully catches on.

The Final Frontier’s Biggest Bottleneck

When Elon Musk called memory “the limiting factor” for SpaceX’s AI ambitions, he wasn’t talking about some obscure engineering problem.

He was describing a challenge that now confronts virtually every company trying to build the next generation of artificial intelligence.

SpaceX wants to become much more than a launch company. Musk envisions it operating enormous AI data centers, processing data gathered by Starlink’s thousands of satellites, developing autonomous spacecraft, and ultimately creating an AI infrastructure business that extends well beyond Earth’s atmosphere.

But none of that can happen without memory.

Modern AI systems rely on three essential building blocks:

• GPUs, like Nvidia’s AI accelerators, which perform the calculations.
• HBM (high-bandwidth memory), the ultrafast memory attached directly to those GPUs.
• DRAM (dynamic random access memory), the working memory that allows AI models to “think” in real time.

The first bottleneck of the AI boom was compute. Nvidia Corp. (NVDA) became one of the world’s most valuable companies by solving that problem.

That bottleneck has shifted. Now it’s memory.

Large language models don’t simply perform calculations. They must constantly store, retrieve, and manipulate staggering amounts of information while generating each response.

Training a ChatGPT-sized model can require tens or even hundreds of terabytes of DRAM spread across thousands of GPUs. Without enough memory, those expensive AI systems simply wait.

No memory means no intelligence.

That’s why Nvidia CEO Jensen Huang recently warned that the industry’s “memory bottleneck is severe.”

It’s also why tech companies have reportedly stationed employees in South Korea for months at a time, hoping to secure scarce DRAM allocations from Samsung and SK Hynix Inc. (SKHY). The industry has even given these buyers a nickname: “DRAM beggars.”

SpaceX may have been the first company to say it publicly, but it certainly won’t be the last.

One of the Companies Solving the Memory Problem

The numbers explain why.

Nearly 100 gigawatts of new AI data centers are expected to come online over the next four years. Yet industry estimates suggest there is enough DRAM supply to support only about 15 gigawatts of new capacity over the next two years.

That imbalance is already driving prices sharply higher. Market researcher TrendForce expects conventional DRAM contract prices to surge 90% to 95% in early 2026, one of the fastest increases the industry has ever experienced.

During SpaceX’s earnings call, Musk added another eye-opening statistic. He expects AI memory demand to grow at nearly 200% annually.

That combination – exploding demand and constrained supply – is exactly the sort of bottleneck I like to look for as an investor.

One company I’ve got my eye on is PDF Solutions Inc. (PDFS).

Unlike memory manufacturers themselves, PDF Solutions helps semiconductor companies produce more usable chips from every manufacturing run. Its software identifies defects, improves manufacturing yields, and helps chipmakers reduce costly failures. Those are capabilities that become dramatically more valuable when every additional AI memory chip commands a premium.

As manufacturers race to increase DRAM and HBM production, companies like PDF Solutions quietly become indispensable behind the scenes.

That’s one reason PDFS has become one of the most interesting memory-related stocks I’m watching.

It isn’t the only one.

Where I Think the Next Winners Will Come From

If you’ve followed my work for any length of time, you know I spend very little time chasing whatever Wall Street already loves.

Instead, I look for the bottlenecks.

Years ago, that meant identifying Nvidia before most investors appreciated how valuable AI compute would become.

Last year, it meant recognizing that the AI trade was entering a new phase, one where the biggest gains would increasingly come from the companies supplying what I call AI’s Golden Rivets. Those are the irreplaceable materials, energy, networking, and memory infrastructure every AI company depends upon.

Today, I believe we’re entering the next phase of that acceleration.

Much like the astronomers who assumed the universe’s expansion would gradually slow, I believe many investors are underestimating what’s happening today. They see AI continuing to grow, but they haven’t yet recognized how quickly demand for the infrastructure supporting that growth is accelerating.

And as we’ve already seen with SpaceX, those accelerating demands are beginning to expose entirely new bottlenecks… and entirely new investment opportunities.

In my latest Market Shock presentation, I explain that while the AI Revolution is still in its early innings, the next big winners are unlikely to be the same companies that dominated the last three years.

I’ll also share four memory-related stocks I believe are positioned to benefit from this bottleneck, including three additional names and tickers beyond PDF Solutions that I’m watching very closely.

If you’d like to see the complete framework, and why I believe SpaceX’s earnings call may have revealed far more than Wall Street realizes, you can watch that free presentation here.

Regards,

Eric Fry

Editor, The Speculator

P.S. Eric Fry has spent decades identifying major market shifts before they become obvious. His latest research suggests the next big winners won’t be the companies dominating today’s AI headlines, but the businesses supplying the critical infrastructure the entire industry depends on. If you enjoyed today’s essay, I think you’ll find his free Market Shock presentation well worth your time. In it, Eric explains his full thesis and shares several additional stocks he believes are positioned to benefit from AI’s next phase. Find it here.

The post 4 Stocks That Could Profit From SpaceX’s Biggest Problem appeared first on InvestorPlace.

It’s a few hundred miles straight up.

Alongside its debut earnings report this week, SpaceX (SPCX) announced that it’s teaming up with Nvidia (NVDA) to design the compute payload for Starmind AI1 – the first satellite in a planned orbiting network built to run AI workloads in outer space. 

Importantly, this isn’t a research payload or a proof-of-concept demo. Starmind AI1 is designed to run production AI workloads in orbit – on Nvidia’s top-of-the-line Vera CPUs, Rubin GPUs, and the Vera Rubin NVL72 rackscale system, the same architecture powering the most advanced AI data centers on Earth. 

And on SpaceX’s Q2 earnings call, Elon Musk went out of his way to shut down the sci-fi talk before the bears could even start. He said the Starmind satellite “is not some sort of far future distant thing.” SpaceX expects to start launching next year.

Now, we don’t take Musk timelines at face value. The man’s deadlines are aspirational by design. He’s missed enough of them that “Elon time” is now a popular term on Wall Street. Pencil in delays.

But the timeline isn’t the story. The commitment is.

Because back in April, we published a deep dive making the case that AI was living through its “generator moment” – that the binding constraints on AI’s growth are land, power, and water, and that the next grid wouldn’t be built on the ground at all. It would be built in orbit.

At the time, that was a thesis.

Four months later, it’s become more of a procurement schedule.

How Space Data Centers Moved From Thesis to Roadmap

Here’s what has happened since we published that first piece. Notice how the announcements keep moving down the stack, from filings to hardware to launch manifests:

In late April, Meta (META) signed a deal with Overview Energy to deliver a gigawatt of beamed power from space – Big Tech’s first purchase order for space-based energy. Blue Origin filed for its own constellation of 51,600 data center satellites. Alphabet‘s (GOOGL) Project Suncatcher – which pairs its custom TPUs with Planet Labs (PL) satellite hardware – completed radiation testing showing its chips can survive a five-year orbital mission, with two prototype satellites slated for early 2027. Starcloud, which trained the first language model in space last December on a single H100, launches Starcloud-2 in October with roughly 100 times the power generation and Nvidia’s newer architecture on board.

Then, in July, Intel (INTC) debuted Starfire: a radiation-hardened processor purpose-built for space computing, integrating CPU, graphics, neural, and image processing to let spacecraft run sophisticated AI workloads with less size, weight, and power. It’s expected to reach initial customers by year-end, designed for missions lasting more than a decade, and Intel has already signed partnership agreements with multiple government organizations. Notably, Intel Government Technologies’ Sean O’Neill framed the ambition as being partners, not just a component vendor.

Read that list again. Then ask yourself one question: do chipmakers build entire product lines for markets they don’t believe exist?

When both Nvidia and Intel – America’s most iconic chipmakers – are shipping silicon designed to survive radiation and vacuum , orbital compute has crossed the line from “thesis” to “roadmap.”

Why SpaceX’s Starmind AI1 Changes the Orbital Data Center Thesis

Of everything that’s happened since April, the Starmind announcement is arguably the most important – and not for the reason you might think.

The headline is “data center in space.” The tell is buried in Musk’s commentary about the architecture. 

SpaceX has decided to build exclusively on Nvidia’s Vera Rubin platform, and Musk says the optimized NVL72 design that flies on Starmind will be deployed on the ground as well as in orbit – because SpaceX views it as a radical simplification of the standard rack.

That means orbital compute is no longer being designed as some exotic, bespoke science project. It’s becoming a variant of the standard AI buildout – same chips, same racks, same software stack, different address. That’s how infrastructure transitions actually happen: not with a moonshot that replaces the old system, but with a standardized platform that can live in either environment and simply flows toward wherever power and cooling are cheapest.

And as we detailed in April, the direction of “cheapest” is not in dispute. Terrestrial compute costs are resource-bound – hostage to interconnection queues, water rights, and land scarcity – and they reliably rise. Orbital compute costs are technology-bound – hostage mainly to dollars-per-kilogram to orbit – and they reliably fall.

The Reality Check

Let’s be equally clear-eyed about what hasn’t changed: the economics still favor Earth. Today, by a lot.

The most rigorous independent look at this question, from SemiAnalysis in early June, pegs orbital compute at more than 4x terrestrial cost right now – roughly $8.64 versus $2.37 per GPU-hour for a comparable cluster – driven by launch costs and the shorter useful life of hardware in orbit. Their base case sees the premium narrowing to about 30% by the early 2030s, with full cost parity arriving around 2040. Optimists argue specific workloads pencil out as soon as 2028-2030. Skeptics – including engineers at Varda Space Industries – counter that orbit still runs roughly 3x more per watt.

Our own April analysis put the crossover around 2038, potentially pulling forward to 2036 as competition compresses launch costs. We stand by that range. And frankly, the fact that serious analysts are now fighting over which year parity arrives – rather than whether it arrives – is perhaps the most bullish development of all. Wall Street doesn’t argue this hard over things it plans to ignore. 

Just as important: the early market doesn’t need parity to form. Defense and space-based sensing programs need compute close to the sensor. Earth-observation workloads waste enormous downlink bandwidth shipping raw data to the ground. For those buyers, orbital compute is already the practical answer.

The Space Data Center Stocks Positioned to Benefit

So, how do we position? Mostly, the same way we laid out in April – but this week’s news reshuffles the pecking order.

Nvidia just picked up something the bears never model: a brand-new source of demand that isn’t in anyone’s model. Every Starmind-class satellite is an NVL72 system sold into a market that didn’t exist a year ago. And SpaceX standardizing exclusively on Vera Rubin is one of the more underappreciated design wins of this cycle.

Intel is now on the board. We’re not ready to call Starfire a thesis-changer for a company with Intel’s broader challenges. But a space chip built to run for a decade-plus, with government partnerships already signed, is a real foothold in this market. Watch the customer announcements.

Microchip Technology (MCHP) remains the most underappreciated name in the stack. It’s the dominant supplier of the radiation-hardened FPGAs that virtually every satellite needs, growing space revenue roughly 40% a year with almost no one covering it as an orbital compute play.

Rocket Lab (RKLB) and Redwire (RDW) are the purest picks-and-shovels plays. Every orbital data center has to be launched. And every one of them is, functionally, a flying power plant – which is exactly Redwire’s lane, as the maker of the ROSA solar arrays already proven on the International Space Station. Both stocks were hammered in the recent space selloff. As we wrote after SpaceX’s Q2 report, their charts are starting to act like they want to come back.

Planet Labs gets a quiet upgrade, too. Every Suncatcher milestone Google hits makes PL’s seat at that table more valuable.

One Housekeeping Note

In April, we recommended pre-IPO wrappers – the Tema Space Innovators ETF (NASA), DXYZ, XOVR – as the way to own SpaceX before it listed, with instructions to trim aggressively at the IPO. That trade has now played out. SpaceX trades under its own ticker. And with shares down as much as 32% from their post-IPO highs, investors finally get to buy the orbital compute flagship directly – at a discount to the euphoria, though with all the volatility and capex-driven turbulence we flagged in our earnings breakdown.

The Bottom Line: Orbital Compute Has Entered the Roadmap Phase

Every infrastructure transition follows the same arc: dismissed as fantasy, debated as economics, and then suddenly discussed as logistics.

Orbital compute just entered phase three. The chips exist. The regulatory filings are in. Prototypes are being tested, the launch dates are on calendars, and the two biggest names in AI hardware are building for it in silicon.

Will Starmind launch on Musk’s schedule? Probably not. Will the economics flip next year? No – the honest math says the crossover is still years away.

But the market never waits for the crossover. It prices the trajectory. 

And that’s exactly why I’ve been pounding the table on this moment.

Because everything we just walked through – the chips, the filings, the launch dates – is converging on what I believe is the single biggest wealth-creation setup of this cycle. I call it “XPANSE.”

It’s a project so enormous that Elon himself believes it could make early investors [1,000 times their money.

And the stakes go far beyond your portfolio. Right now, the entire AI economy rests on infrastructure that’s dangerously concentrated and dangerously constrained – a looming threat that one high-ranking government official has dubbed “an economic apocalypse.” XPANSE could be how America eliminates that threat before it detonates.

You don’t need to guess your way into this. In my new briefing, I lay out the three steps you must take today to get on the right side of this shift – and I give away the name and ticker of an investment perfectly positioned to capitalize on it, completely free.

The grid is going up whether you’re positioned or not. Which side of the trajectory will you be on?

The post SpaceX Just Put a Launch Date on the Orbital AI Boom appeared first on InvestorPlace.

This morning brought the latest Challenger, Gray & Christmas jobs report and, overall, the numbers look encouraging.

If you’re less familiar, Challenger, Gray & Christmas is an outplacement and executive coaching firm that tracks and analyzes corporate layoffs across the United States. Its monthly Challenger Employment Report serves as an early, reliable indicator of labor market trends.

This morning, the report showed that employers announced just 33,429 job cuts in July – down 27% from June and down 46% from a year ago. It was the lowest monthly total in two years. Meanwhile, hiring plans jumped 47% from June, the strongest July for hiring since 2022.

But look past the headline, and AI’s fingerprint on job losses keeps growing…

AI was the No. 1 cited reason for job cuts for the fifth consecutive month (March through July), responsible for 10,970 cuts in July alone – 33% of the month’s total.

So far this year, AI has been blamed for 112,713 job cuts. That’s almost a quarter of all U.S. layoffs, up about 23% from a month ago. And it’s already more than double the 54,836 AI-related cuts recorded in all of 2025.

So, how do we interpret this?

Well, it’s not an AI “jobpocalypse” with bots directly kicking humans out of the workforce. But neither is it business as usual…

Tech giants and financial institutions are freezing traditional hiring and quietly cutting departments to fund massive AI infrastructure spending.

Regular Digest readers know that my thinking on this is evolving. Two years ago, I expected AI-driven layoffs to show up loudly, visibly, and consistently. There have been some loud, visible announcements – but not consistently. Of course, that doesn’t mean it won’t happen.

The trouble is every new jobs report or corporate announcement – viewed narrowly – leaves us unclear whether we’re looking at “noise” or the early stages of something bigger. So instead of reacting to every new headline, I built a framework to help us.

It puts each new data point in context: a map of the stages an AI-driven jobpocalypse would likely move through, so we can better identify where we are in this process.

The 7 stages of an AI jobpocalypse

It’s less of a prediction and more like a diagnostic.

So, here’s the map, running from mildest to most severe:

Stage 7 is the one everyone fears. It’s not guaranteed – even where AI could technically do the work that new growth creates, companies still have to choose to automate it rather than keep people. Customer trust, regulatory pressure, and plain political risk could be a deterrent against squeezing out every last efficiency gain. But we’ll see.

One note – these stages won’t play out in perfect order; some will overlap. But from 30,000 feet, this is likely the shape an AI-driven jobpocalypse would take.

Where are we today?

We’re seeing data from stages 1 through 3 show up, with hints of stage 4.

For example, the 2026 Fortune 500 rankings – based on companies’ most recent fiscal-year results (mostly fiscal 2025) – show revenue hit a record $21 trillion and profits a record $2.1 trillion, both up from the prior year’s list. Yet collective headcount fell for the second year in a row, a loss of more than 301,000 jobs.

Revenue and profit climbing while headcount shrinks are stages 1 and 2, playing out in plain sight across America’s largest companies. (Some of that reflects a longer efficiency trend that predates AI – but the size and direction of the gap fit the pattern.)

For stage 3, Stanford researchers tracking 25 million workers found employment among 22-to-25-year-olds in the most AI-exposed occupations down 13% since 2022 – and for young software developers specifically, down nearly 20% since 2024, even as hiring for more experienced developers in the same firms keeps growing.

Again, these aren’t firings; rather, they’re a closing of the door to the next generation of workers.

To be fair, a May New York Fed study found no clear divergence between junior and senior job postings in AI-exposed occupations – and noted the broader decline in those postings predates ChatGPT’s release.

As to stage 4, there are early signs of this, too. Last year, Shopify (SHOP) CEO Tobi Lütke told his staff that “reflexive AI usage is now a baseline expectation” – teams must justify headcount by proving AI can’t already do the work.

A year later, Shopify’s headcount has fallen from roughly 8,100 to roughly 7,600 while revenue has grown about 30% to $11.6 billion, pushing revenue per employee to around $1.5 million.

Now, tomorrow brings the Bureau of Labor Statistics’ official nonfarm payrolls report. It won’t show any dramatic AI-driven collapse – but it’s not built to catch one.

A single monthly headline measures the whole economy at once; our 7-stage framework measures something narrower and, frankly, more useful – where AI is quietly reshaping hiring and headcount before any of it shows up as a scary topline number. We want to measure the churn beneath the smooth surface.

So, over the coming quarters, watch headline numbers less and listen for explanations more. When the “why” behind corporate hiring and firing starts to sound like stage 3 or 4 with increasing volume, that’s your tip-off that stages 5 and 6 won’t be far behind.

We’ll keep tracking it.

Last call for Luke Lango’s 2026 AI Megadeal Event

Most investors assume the best way to profit from AI is by buying the companies everyone already knows – Nvidia (NVDA), OpenAI, Anthropic, or the next high-profile AI stock.

Our technology expert Luke Lango sees it differently.

At last Thursday’s 2026 AI Megadeal Event, he explained how AI is creating an entirely new layer of wealth creation that exists largely outside the public stock market. As Big Tech races to acquire breakthrough technologies, enormous value is being created long before most investors ever have the chance to buy a single share.

During last week’s event, Luke laid out how today’s AI wealth is increasingly being created through acquisitions of small, private companies – the breakthrough technologies larger firms are eager to own. More importantly, he detailed how ordinary investors can position themselves for it.

As part of the presentation, Luke gave away the name of a robotics startup whose clients include Nvidia (NVDA), Microsoft (MSFT), Salesforce (CRM), and the Mayo Clinic.

Here’s Luke:

Its one-of-a-kind ‘robot school’ platform is rolling out now, and I believe this represents the “ChatGPT moment” for artificially intelligent robots.

I project this startup’s revenue could grow from approximately $18 million by the end of this year to as much as $360 billion by 2029.

But this is just one opportunity. AI is creating many more – and Luke has built a framework specifically to spot them before the rest of the market catches on.

The free replay of last Thursday’s presentation is still available to watch here – but not for long. We’re taking it offline tonight at midnight.

So, if you’ve been meaning to watch it, this is your last call.

On Wednesday, Point72 Asset Management told investors it had been attacked

It wasn’t the only investing firm attacked. Two Sigma Investments, Citadel, and several private equity firms were also targeted.

It was part of a series of sophisticated attacks on Wall Street firms in recent days that targeted information systems.

Here’s Bloomberg:

The attack featured voice phishing, or vishing, in which cyber criminals use technology to mimic voices in phone calls or messages to trick employees into revealing sensitive information or granting access.

This isn’t surprising. We’ve been tracking the growth of cyberhacks here in the Digest for years.

Most recently, back in May, Money & Megatrends editor Brian Hunt wrote about the problem:

Today, a fraudster can generate a realistic fake ID in seconds and clone someone’s voice from three seconds of audio. The fraudster can also use AI to create a deepfake video that blinks, turns, and smiles on command.

These nefarious products can allow them to bypass security checks that banks and financial institutions rely on to verify identity…

Scores of statistics reveal how big a problem this is becoming.

As just one example, Peris.ai reports that deepfake voice attacks drained $1.1 billion from U.S. corporate accounts last year, tripling 2024’s figure of $360 million.

And it’s not just corporations – individuals need to be on alert too. According to SQ Magazine, U.S. consumers receive 9.9 unwanted calls per week on average, or more than 500 per year. Overall, multi-channel phishing campaigns combining voice, SMS, and email jumped 97% last year.

But perhaps the most frightening statistic of all of this comes from Programs.com:

Even when warned of the dangers of voice phishing, 33% of people still disclose sensitive information during an attack.

Think about that: one out of three will know the attack is coming – and still fall for it.

All this points toward one thing…

Cybersecurity is a must-have – which makes it a must-have in your portfolio.

How to invest today

If you want the one-click-and-you’re-done option, check out the Amplify Cybersecurity ETF (HACK). It holds cybersecurity heavyweights including Palo Alto Networks (PANW), Cisco (CSCO), and Cloudflare (NET).

But if you’re looking for concentrated exposure, Brian has an idea – Mitek Systems (MITK), a stock he profiled months ago.

From his Money & Megatrends issue back in May:

Mitek is a $640 million company with a 25-year head start on this challenge.

Its legacy business – processing over one billion mobile deposits annually – has made it the trusted identity backbone for many North American financial institutions.

Major customers include JPMorgan Chase, Bank of America, PayPal, and Capital One…

Its Verified Identity Platform brings together identity document authentication, biometric liveness detection, deepfake and voice-clone scoring, and real-time fraud analytics.

As I write, it’s up nearly 16% since Brian flagged it in Money & Megatrends, quadrupling the S&P over the same period.

Based on how rapidly cyberattacks are increasing, these gains are likely just the beginning.

We’re running long, so I won’t go deeper into Brian’s analysis, but I encourage you to. Here’s his issue that profiled MITK.

And for more from Brian, you can sign up for his Money & Megatrends newsletter right here. Every day the market is open, he delivers actionable insights, loaded with specific stock tickers. Best of all, it’s 100% free.

In addition, Brian has published a free special report on stocks that could be the biggest beneficiaries of AI job displacement. You can find that on his Money & Megatrends site right here.

We’ll keep you updated on all these stories here in the Digest.

Have a good evening,

Jeff Remsburg

(Disclosure: I own HACK and MSFT)

The post The 7 Stages of the Jobpocalypse and How to Spot What Comes Next appeared first on InvestorPlace.

Three elderly women examine a massive hamburger bun. But when the top is removed, they find a very small hamburger patty.

One of the women famously shouts, “Where’s the beef?”

Ever since then, “Where’s the beef?” has been a catchphrase for looking past the hype and finding the real substance underneath.

Interestingly, that’s exactly what I’ve done my entire career.

Every day, Wall Street is inundated with headlines, opinions and predictions. One day, it’s geopolitical tensions. The next, it’s interest-rate speculation, Federal Reserve policy, inflation or the latest market rotation.

But earnings season cuts through that noise. It shows us which companies are actually growing – and where the money is really flowing.

That’s why when earnings season rolls around, it’s my job to look past the distractions and answer one simple question: “Where’s the beef?”

Or said another way: Where is the real earnings growth?

Earnings announcement season is one of the most important times of the year for investors. It’s also my favorite time of year because opinions finally give way to facts.

And the facts are becoming increasingly clear.

We’re in the midst of one of the strongest earnings environments of my lifetime.

And artificial intelligence remains one of its biggest driving forces.

AI demand is spreading throughout the technology stack and into the physical infrastructure needed to support it – from processors and data storage to power generation and grid equipment.

And this week’s results from Advanced Micro Devices, Inc. (AMD) and SanDisk Corporation (SNDK) offer two important clues about how far that demand has spread.

In today’s Market 360, we’ll examine the strongest earnings growth in five years, what the latest results reveal about the AI buildout and why some of its biggest beneficiaries may sit outside the best-known chip and software stocks.

The Strongest Earnings Growth in Five Years

I don’t say “I told you so” very often. But for the past few weeks, I’ve noted that the S&P 500 was on track to achieve average earnings growth north of 30% in the second quarter.

Well, my forecast has already been proven right – and we’re only about halfway through earnings announcement season.

Our friends at FactSet recently reported that current estimates call for the S&P 500 to achieve average earnings growth of 47% in the second quarter. That’s up from estimates of 23.2% just last week and only 18.6% on March 27.

It’s simply stunning, folks.

So, what’s driving this spectacular earnings environment?

Artificial intelligence and the massive data center buildout are playing a major role.

As companies race to develop and deploy increasingly powerful AI models, they need more computing power, more storage capacity and more supporting infrastructure. That demand is producing accelerating sales, expanding order backlogs and spectacular earnings growth throughout the AI ecosystem.

This week, two very different semiconductor companies gave us another opportunity to look beneath the surface and see where AI demand is spreading next.

Two Earnings Reports Offer the Next Clue

Let’s start with the obvious part of the AI stack: semiconductors.

Advanced Micro Devices shares dipped lower on Tuesday afternoon despite the company’s better-than-expected quarterly results. Apparently, Wall Street wanted even stronger revenue growth.

But when we look beneath the stock’s initial reaction, the numbers reveal tremendous demand for AI computing power.

AMD’s data center revenue doubled year-over-year to a record $6.7 billion. The division now accounts for 58% of the company’s total revenue.

Overall revenue rose 50% year-over-year to $11.54 billion, topping estimates of $11.31 billion. It was AMD’s fifth-straight quarter of record revenue.

Second-quarter earnings surged 253% year-over-year to $2.76 billion, or $1.66 per share. Analysts expected earnings of $1.61 per share, so AMD posted a 3.1% earnings surprise.

And management expects data center revenue to accelerate further in the second half of 2026. For the third quarter, AMD anticipates revenue of approximately $13.0 billion, which would represent 41% year-over-year growth.

In other words, Wall Street may have wanted an even bigger quarter. But there is no mistaking where the beef was in AMD’s report.

It was in the data center.

And that same demand showed up in another critical layer of the AI technology stack: data storage.

SanDisk shares also pulled back sharply this morning despite reporting better-than-expected quarterly results. In this case, Wall Street appeared disappointed that the company’s revenue guidance was not even stronger.

But when we look beneath the stock’s initial reaction, the numbers reveal extraordinary demand for the data storage needed to support AI.

For fiscal year 2026, SanDisk reported that data center revenue grew 437% year-over-year to $5.15 billion, while edge revenue jumped 195% year-over-year to $12.16 billion.

For its fourth quarter in fiscal year 2026, total revenue soared 372% year-over-year to $8.97 billion, topping estimates of $8.39 billion. Earnings surged to $6.16 billion, or $39.25 per share. Analysts expected earnings of $34.51 per share, so SanDisk posted a 13.7% earnings surprise.

Looking ahead, SanDisk expects total revenue between $10.3 billion and $10.8 billion and earnings per share between $44 and $46.

SanDisk shares still pulled back after the report, as Wall Street appeared disappointed that guidance was not even stronger. But that a knee-jerk reaction, folks. The company’s first-quarter guidance still calls for revenue growth of 345.9% to 367.5% and earnings growth of more than 3,500%!

So, while AMD’s results underscored the demand for computing power, SanDisk’s report highlighted another critical piece of the AI buildout: storing the enormous volumes of data those systems create.

The AI Boom Reaches the Power Grid

The demand does not stop with processors and storage, though.

Consider GE Vernova Inc. (GEV), one of the world’s leading suppliers of power-generation and electrification equipment.

GE Vernova reported $24.2 billion in second-quarter orders, an 88% increase from the same quarter a year ago. Its total backlog expanded by another $13 billion during the quarter to reach $176 billion.

Data centers are becoming a significant part of that growth. Companies can order all the AI chips they want. But those chips are useless without enough electricity to run them and the grid equipment to deliver that power.

Bloom Energy Corporation (BE) offers another example.

Bloom builds on-site fuel cell systems that help data centers secure reliable power without waiting years for new transmission lines or grid upgrades.

Bloom’s second-quarter revenue surged 165.5% year-over-year to a record $1.07 billion, marking the company’s first billion-dollar quarter. Product revenue jumped 215.4%, while adjusted earnings rose to $0.78 per share from $0.10 a year ago.

Bloom entered 2026 with a backlog of approximately $20 billion, including about $6 billion in product orders and $14 billion in long-term service agreements.

The company only provides a specific backlog figure once a year, so we do not have an updated second-quarter total. But management said backlog is growing faster than revenue.

Together, GE Vernova and Bloom Energy show that the AI spending boom has reached the companies responsible for generating and delivering the electricity behind it.

For the record, we have held both of these names in my Growth Investor service for less than a year. GEV is up by about 63% and BE is up by 225%. 

“Where’s the Beef?”

So, where’s the beef this earnings season?

I gave you just a few examples, but some of the strongest earnings growth is appearing across the entire AI buildout – from cloud computing, advanced processors and data storage to the power systems keeping it all running.

My Stock Grader system currently gives all four stocks a “Strong” or “Very Strong” Total Grade (subscription required).

But these companies only represent the current stage of the AI buildout.

Today’s best AI systems were designed primarily to generate text, images and code. But the federal government is now backing a new scientific-computing effort intended to tackle far more complex work in fields such as energy, medicine and quantum computing.

The project is taking shape across the Department of Energy’s national laboratory network, including the same Tennessee facility that played a central role in the original Manhattan Project.

That means it will require an enormous amount of computing power, data storage, networking equipment and electricity.

In other words, we’re just getting started, folks.

The earnings results we are seeing now show that the infrastructure race is already underway. The next question is which companies will capture the biggest share of the spending as this government-backed scientific AI system comes online.

That’s why I put together a special presentation explaining what I call the AI Reset. In it, I reveal the government project behind this shift, the companies helping to build it – and the stocks my system has identified as the best positioned to benefit.

I’ll also explain why this new system could change what AI is capable of doing – and why investors who focus only on today’s chatbot leaders may miss some of the biggest opportunities ahead.

The earnings tell us where the beef is today. My AI Reset presentation reveals where it may be headed next.

Go here to learn more now.

Sincerely,

Louis Navellier

Editor, Market 360

P.S. My new Stock Grader AI feature is now live – giving you a powerful new way to interact with the system.

You can search for stocks by sector, size, risk profile, grade trends and more, all using plain English. You’ll also receive weekly AI-powered insights highlighting the most important upgrades, downgrades and sector shifts.

Access to this tool is only available to my Preferred Members. If you’re a subscriber of Growth Investor and want to gain access to my new Stock Grader AI tool, learn more about upgrading to a Preferred Membership through this exclusive invitation.

Not a Growth Investor member yet? Learn more about Growth Investor and gain access to Stock Grader AI here.

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

Advanced Micro Devices, Inc. (AMD), Bloom Energy Corporation (BE), GE Vernova Inc. (GEV) and SanDisk Corporation (SNDK)

The post “Where’s the Beef” in This AI Earnings Boom? appeared first on InvestorPlace.

In 1988, Alan Kulwicki – one of NASCAR’s ultimate underdogs – won the Checker 500 at Phoenix International Raceway. To celebrate his victory, he drove his car in the reverse direction of the race to wave directly at the fans.

Many drivers have performed this “Polish Victory Lap” (referencing Kulwicki’s heritage) in the decades since. It is a unique public celebration of success.

Amazon.com Inc. (AMZN) – while not a Wall Street underdog – just celebrated its own victory lap.

The company reported quarterly earnings and revenue that exceeded expectations – $1.97 in adjusted earnings per share and $200 billion in revenue. AWS revenue grew 37% from the same quarter one year ago.

Wall Street cheered Amazon’s results, and the stock jumped 15% to an all-time high.

This milestone pushed the company’s market valuation beyond $3 trillion, joining the ranks of Apple Inc. (AAPL), Microsoft Corp. (MSFT), Nvidia Corp. (NVDA), and Alphabet Inc. (GOOGL).

That’s a genuine achievement.

It’s also a double-edged sword.

There’s a downside to success, especially in the form of an earnings beat: The crowd immediately expects another, and that is getting increasingly harder to deliver.

So, in today’s Smart Money, I’d like to explain why, despite Amazon’s earnings beat, I’m not changing my “Sell” rating on the company – and why recent developments have only strengthened that view.

Then, I’ll let you in on another e-commerce company that deserves a spot in your portfolio.

Let’s jump in…

The $3 Trillion Illusion

Although Amazon beat expectations, its earnings weren’t as impressive as they first appeared.

About $53.4 billion of its $62.6 billion profit didn’t come from selling more products or growing its core businesses. Instead, it came mostly from an increase in the value of its Anthropic investment.

Meanwhile, the cost of staying in the AI race went up.

Amazon raised its full-year capital expenditure (CapEx) guidance to roughly $220 billion, up from $200 billion, citing rising memory costs. That means the company will need even bigger future profits to justify that spending.

Every dollar Amazon spends on AI raises expectations for what that spending needs to deliver. Investors aren’t just betting on Amazon’s current profits – they’re betting that its AI investments will create much bigger profits in the future.

The challenge is that Amazon now needs AI to generate enough returns to justify both its $220 billion spending plan and its $3 trillion valuation.

Amazon also isn’t running this race by itself. Big Tech is pouring billions into AI infrastructure. Each company is competing for the same customers, talent, and supply of advanced chips.

We’ve been tracking this AI spending race here at Smart Money. And as the stakes get higher, the margin for error gets smaller. A $3 trillion company has far less room for error than a $300 billion company. When expectations are this high, “good” results often aren’t good enough for long.

That is exactly what makes Amazon vulnerable. And why I continue to classify it as a “Sell.”

Even founder Jeff Bezos seems to be following the same track. One day after Amazon crossed the $3 trillion market cap mark, Bezos filed to sell around $4 billion of his own shares – roughly 15 million.

Now, to be fair, this wasn’t a snap decision. The plan was adopted back in November 2025, and Bezos has been steadily trimming his stake for years. He sold another 25 million shares for nearly $5.5 billion this past June.

But that’s exactly the point.

The man who used to be in the company’s driver’s seat hasn’t stopped selling. That suggests he doesn’t see unlimited upside from here.

Of course, this doesn’t mean Bezos expects Amazon to collapse. But it does reinforce a broader point: When expectations are this high and insiders are selling, investors should ask whether the easy gains are already in the rear-view mirror.

Victory laps are driven after the race is won. But for Amazon, the race isn’t over.

That’s why I’m looking elsewhere for opportunity. And I’ve found an e-commerce company growing even faster than Amazon in the world’s most connected economy…

Where the Real AI Money Is Moving

Even though this firm isn’t a household name here in the U.S., it is well known in every Korean household as the go-to provider of Amazon-like services. 

I call it the “Amazon of South Korea.”

Projections are showing it could become 700% more profitable by 2027. And it already generates over $30 billion in revenue but trades at a tiny fraction of Amazon’s valuation. 

It’s like finding Amazon in 2005, but with a bigger competitive advantage and stronger momentum.

I reveal the name of this recommendation free of charge in my Sell This, Buy That presentation.

Investors are beginning to recognize that the most lucrative AI opportunities often lie beyond the companies that drain their balance sheets to maintain their top position.

It’s why I’ve been recommending the overlooked stocks that are well-positioned to benefit in the AI era and why I’m avoiding the big players like Amazon.

As the major tech giants attempt to maintain their position in the AI race, click here to see the types of stocks I recommend you watch instead.

Regards,

Eric Fry

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The company had just bled roughly $1 billion of cash in a single quarter – the latest installment in a free-cash-flow bonfire that had consumed some $24 billion since 2011. And after a furious Model 3 production ramp in late 2018, Wall Street took the early ‘19 delivery slump as a harbinger of doom. 

Yet, beneath all the noise, the machine kept whirring. Deliveries were scaling. Gigafactory Shanghai came online, with the first production vehicles rolling out less than a year after breaking ground. Tesla’s stock was falling, but its technology lead kept growing.

Here’s what I wrote in June 2019: 

“All in all, not only is the Tesla growth narrative far from dead, but it’s about to get a lot better. As it does, I wouldn’t be surprised to see TSLA stock rally back towards $300.”

You know what happened next. 

Within two years, TSLA stock rallied more than 20-fold, and the people who got paid weren’t the ones who were right about the quarter. They were the ones who were right about the decade.

I bring this up because we just watched Elon Musk report earnings twice in two weeks – once at Tesla, and once at the newly public SpaceX (SPCX). 

Both reports carried the exact same growth profile: explosive top-line growth, ugly bottom-line optics, gargantuan capex, and a market of investors who can’t decide whether they’re looking at a money pit or the ground floor of an empire.

Let’s break down both – and, more importantly, let’s talk about where I think the real torque is hiding.

Tesla Earnings Show the Musk Reinvestment Blueprint

Tesla’s second-quarter report on July 22 was like a study in contradiction.

The top line was a monster. Revenue hit a record $28.2 billion, up 26% year-over-year – the company’s first real growth inflection in over a year – on a Q2-record 480,126 vehicle deliveries that blew past estimates. Energy storage deployments jumped more than 40% to 13.5 gigawatt-hours. Services revenue surged 50% to record profitability. And Tesla crossed $100 billion in trailing-twelve-month revenue for the first time in its history.

Meanwhile, the bottom line? A mess. Operating income cratered 57% to just $398 million, compressing operating margins to a razor-thin 1.4%. Adjusted EPS of $0.33 badly missed the ~$0.51 consensus. Regulatory credits – once a reliable profit cushion – collapsed to $146 million from $439 million a year ago. Capex exploded 142% to $5.8 billion, and free cash flow swung negative by about $1.1 billion.

So, which is it: a broken profit engine, or a company reinvesting everything into what comes next?

Look at where the money went: Cybercab production starting at Giga Texas. Robotaxi operations now live in seven metro areas. First-generation Optimus production lines being installed. AI infrastructure spend ramping across the board. Tesla isn’t losing its profitability. It’s spending its profitability – aggressively and all at once – to fund the Physical AI era.

Sound familiar? It should. Because Musk’s other trillion-dollar company just did the exact same thing.

SpaceX Earnings: 92% Growth and an $18.4 Billion Spending Bill

SpaceX’s first earnings report as a public company was, directionally speaking, everything the bulls could have asked for.

Revenue surged 92% year-over-year to $7.8 billion. Adjusted EBITDA nearly tripled to $3.5 billion. Starlink subscribers doubled to 12 million. Enterprise and government connectivity revenue jumped 108%, and Starshield locked in more than $6 billion of new contracts.

But the showstopper was AI. SpaceX’s AI revenue soared 247% to $2.6 billion, and the segment swung to $1.1 billion of positive adjusted EBITDA. Management has already signed another $6.7 billion of cloud business in Q3, with new compute investments paying back in under a year. The company expects compute capacity to exceed 2 gigawatts this year and approach 10 gigawatts by the end of 2027.

The integrated space-connectivity-AI flywheel isn’t a slide-deck fantasy anymore. This quarter put real numbers behind it.

Now, was it a clean “all clear” for the stock? No. SpaceX spent a staggering $18.4 billion in the quarter – $15.8 billion of it on AI – and expects similarly elevated capex for at least two more quarters. The company is still GAAP-loss-making. Some of those shiny cloud contracts contain easy exit clauses. And a looming insider-share unlock hangs over a stock that has been in free fall since its IPO.

In other words, SPCX has the same fingerprint as TSLA – enormous growth, enormous spend, and near-term optics ugly enough to keep the tourists away.

SPCX Stock Is a Time-Horizon Trade

On a six-to-12-month horizon, these are frustrating stocks. Cash-flow optics are ugly. Execution risk is extreme. Every headline is a landmine. There are probably better places for short-term investors to park their money.

Now, on a five-to-10-year horizon, this is exactly what empire-building looks like. Tesla in 2019 looked like a cash bonfire right up until it looked like the best trade of the decade. Musk’s companies have always traded today’s income statement for tomorrow’s market position – and history has, so far, rewarded the patient side of that trade.

Your outlook on TSLA and SPCX will depend almost entirely on which of those two investors you are.

But here’s the thing. I’m actually less interested in what SpaceX’s report said about SpaceX and far more interested in what it said about everyone else.

What SpaceX Earnings Mean for Rocket Lab, Redwire, and Other Space Stocks

SpaceX is already a trillion-dollar-plus company. Even in a raging bull market for space, its upside is governed by the law of large numbers.

The smaller space stocks – Rocket Lab (RKLB), Redwire (RDW), Planet Labs (PL), BlackSky (BKSY), AST SpaceMobile (ASTS) – are not. In a bullish regime, those names carry dramatically more upside torque over the next 12 months. And this earnings report may have just flipped the regime back to bullish, because it put real, strong numbers behind the space economy bull thesis.

Commercial space is graduating from being a speculative science project, to a scaled, economically viable infrastructure market with multi-billion-dollar profit potential. And with SpaceX progressing toward rapid Starship reusability, launch costs could collapse, unlocking an explosion in satellite deployments, constellation refreshes, orbital computing, and space-based services.

Rocket Lab and Redwire: The Strongest Earnings Readthrough

Rocket Lab and Redwire get the cleanest readthrough. For RKLB, SpaceX just validated the vertically integrated launch-and-space-systems model, accelerating constellation demand, and an enormous national-security opportunity – with Neutron positioned as a strategically important alternative to SpaceX itself. RDW may be an even purer picks-and-shovels play: more satellites, orbital data centers, and lunar infrastructure all mean more demand for Redwire’s power systems, components, and in-space infrastructure. Both stocks have been hammered 50%-plus over the past one to two months – and both charts are starting to act like they want to stage a serious comeback. They’re my favorites in the group right now.

Planet Labs and BlackSky: Government Demand Is Expanding

Planet Labs and BlackSky get a strong readthrough, too. Starshield’s $6 billion-plus in new awards confirms governments are racing to embrace commercial space architectures for communications, sensing, and intelligence. That supports PL’s daily Earth-data, sovereign-satellite, and defense businesses, and strengthens demand for BKSY’s high-frequency Gen-3 imagery and AI-powered intelligence platform. Yes, SpaceX’s expanding sensing ambitions create competitive risk, particularly for BKSY. But the bigger takeaway is that the addressable market for real-time space intelligence is growing fast enough to support multiple differentiated winners. Both stocks have also been decimated 50%-plus, and both charts are perking up. Also favorites.

AST SpaceMobile: Validation With a Competitive Warning

AST SpaceMobile is the one exception where the readthrough is mixed. SpaceX emphatically validated the enormous direct-to-device opportunity – but it also unveiled a much more aggressive Starlink Mobile roadmap built on next-gen satellites, owned spectrum, and terrestrial infrastructure. That intensifies the competitive threat to ASTS, even as AST retains real differentiation through its carrier partnerships, broadband-first architecture, and global spectrum position. It remains one of my favorite long-term plays in the group. However, between the competition risk and a rather mixed chart, the next few months could be choppy.

The Bottom Line: Own the SpaceX Earnings Readthrough, Not Just the Rocket

SpaceX is both the rising tide lifting the entire space economy and the shark swimming within it. That’s strongly bullish for infrastructure suppliers and differentiated platforms – and I like the dip-buy setups forming right now in RKLB, RDW, BKSY, and PL.

But if I’m being honest with you, the most important takeaway from these two earnings reports isn’t any single stock. It’s the pattern that connects them.

Tesla and SpaceX just showed us the same movie twice over: sacrifice the quarter, build the empire. Two trillion-dollar companies, run by the same man, pouring every available dollar into the same handful of converging technologies – AI, compute, energy, autonomy, orbit.

That’s the blueprint.

And it’s the reason I’ve spent the past several months digging into what I believe is the single biggest opportunity hiding inside the Musk universe…

What happened when SpaceX finally hit the public market? Remember, it priced its IPO at $135 on June 12, raising roughly $75 billion at a $1.77 trillion opening valuation. Then SPCX stock ripped toward $226… before it gave back as much as 32% from the highs. 

On the one hand, tourists saw a broken IPO. On the other hand, I see a coiled spring. 

SpaceX president and chief operating officer Gwynne Shotwell has spoken openly about a convergence between SpaceX and Tesla – two Musk empires increasingly building toward the same future. Wall Street is already choosing sides on how far that convergence goes, with Wedbush pounding the table, and Oppenheimer pushing back.

I believe that convergence points directly at what I call “XPANSE” – a project so big that Elon himself believes it could make early investors 1,000 times their money.

It’s the same project that could help America eliminate a looming threat one high-ranking government official has dubbed “an economic apocalypse.”

In my new briefing, I lay out the three steps you must take to get on the right side of this shift and give away the name and ticker symbol of an investment perfectly positioned to capitalize on it.

Click here to check out the full briefing.

The post SpaceX’s First Earnings Report Was Better News for Rocket Lab Than SpaceX appeared first on InvestorPlace.

This morning, Minneapolis Federal Reserve President Neel Kashkari went full hawk:

Corporate earnings are through the roof. They’re doing great. The consumer is hanging in there. The labor market is hanging in there.

I look at this constellation and I say, what evidence do I have that monetary policy is particularly restrictive right now?

So, I argued now is the time to start slowly moving up as we get more data in.

Apparently, Kashkari missed the other news this morning – the weakest ADP jobs report since January.

The data showed private companies adding just 44,000 positions in July, well below the expectation for 75,000. It’s a sharp deceleration in hiring momentum and the slowest pace of job growth since the start of the year.

Plus, if we dig into the data, there’s more reason to be skeptical about Kashkari’s confidence…

Goods-producing sectors shrank, shedding a net 3,000 jobs. And in service-providing companies, just two sectors – education and health services – generated 36,000 of the 47,000 new positions.

Does this sound like a red-hot jobs market crying out for higher rates?

Now, the ADP report is an imperfect gauge. The Main Event is Friday, when we get the official nonfarm payroll employment report from the Bureau of Labor Statistics. The forecast is for about 80,000 jobs, which – again – would be on the weaker side relative to historical averages and healthy economic growth.

But that would be good news for legendary investor Louis Navellier. In yesterday’s Growth Investor Flash Alert, after pointing toward estimates for how the number will come in, Louis said:

We kind of want a weak payroll report because we don’t want the Fed to raise rates. We want them to be worried about the labor market.

I don’t sense any worry in Kashkari – or in Cleveland Fed President Beth Hammack or Dallas Fed President Lorie Logan, who were the three FOMC members who just voted for a rate hike at the July meeting.

Still, I’d caution against reading too much into Friday’s payroll report, even if it comes in hotter than expected.

It is really the dawn of a rate-hike cycle?

As I write on Wednesday, the CME Group’s FedWatch Tool shows traders putting nearly 57% odds on a quarter-point interest rate hike in September.

I’m not convinced.

While Kashkari is increasingly hawkish, let’s not forget that new Fed Chair Kevin Warsh has repeatedly emphasized how monetary policy should respond to durable trends rather than monthly noise.

This is also why Warsh places greater weight on inflation measures like the Dallas Fed’s Trimmed Mean PCE inflation gauge, which filters out short-term volatility to better identify the underlying inflation trend.

That philosophy has been applied publicly to inflation, not payrolls. But if Warsh truly prioritizes underlying trends over monthly noise, it’s highly unlikely that one jobs report – strong or weak – will dramatically alter his thinking.

Instead, he’ll pay more attention to the trend in jobs this year, which is uneven, slightly cooling growth.

Another reason why Warsh will push back on a rate hike

The bond market is already doing some of the Fed’s work.

Below, we look at the 10-year Treasury yield – arguably the single most important number in the financial world, as it affects borrowing costs throughout the economy.

Since late June, it has been climbing.

That rise has pushed mortgage rates, corporate borrowing costs, and other longer-term interest rates higher. And tighter financial conditions naturally slow economic activity, reducing the need for the Fed to deliver another increase in its overnight policy rate.

This is precisely the kind of market response Warsh praised after last week’s FOMC meeting.

At his press conference, the new Fed Chair went out of his way to shift the media’s focus from the Fed’s projections to the market’s reaction to incoming information.

From Warsh:

I was comforted that markets in the inter-meeting period weren’t reacting to us. They weren’t reacting to [the Fed’s quarterly dot plot) or to speeches].

They appeared more than ever to be reacting to real-time events, so they’re gauging themselves how restrictive the Treasury curve should be, and that I think has been a useful development.

Warsh appears comfortable with letting the bond market determine how much restraint the economy needs, rather than assuming every strong data point requires another Fed hike.

And according to veteran trader Jonathan Rose of Masters in Trading (MIT) Live, the bond market appears to be doing exactly what Warsh described.

In yesterday’s free MIT episode, Jonathan highlighted that beginning on July 29, shorter-term yields began falling relative to longer-term yields, causing the yield curve to steepen.

Here’s Jonathan:

The Fed didn’t do anything, but the bond market is now trying to force the hand of the Fed.

In other words, in the absence of interest rate changes from Warsh and the Fed, the Treasury market is repricing conditions on its own.

But Jonathan believes investors are viewing this as a constructive development rather than a reason to sell stocks.

Higher long-term yields still raise mortgage rates, corporate borrowing costs, and the discount rate applied to stocks. But the decline at the front end of the yield curve suggests traders are becoming less convinced that the Fed itself must deliver another near-term hike.

In other words, the bond market may be applying restraint where it is needed – through higher long-term borrowing costs – without demanding that Warsh tighten policy further.

So, coming full circle to this Friday’s jobs data, yes, it could move markets in the short run. But between Warsh’s preference for underlying trends and the bond market’s own tightening work, I’m less convinced that the hawkish coalition will win in September.

We’ll report back.

Three experts say it’s time to buy

If Warsh is right that markets – not just the Fed – are determining how restrictive financial conditions should be, then the next question becomes:

What does that mean for investors?

Three of our experts are reading today’s market through three different lenses – technicals, fundamentals, and investor positioning – yet arriving at essentially the same conclusion…

It’s time to buy.

Jonathan is looking at the bond market and the Nasdaq’s price action.

In yesterday’s MIT Live episode, he noted that the Invesco QQQ ETF that tracks the performance of the Nasdaq-100 Index bottomed on July 29 – the same day the yield curve began steepening. He also identified roughly 702 on QQQ as a key support level that now needs to hold, but described the market as firmly positioned on the “long side.”

Here’s Jonathan’s takeaway:

The NASDAQ bottomed the exact same day… And now we are off to the races. 

Now, I wouldn’t take one coincidental market turn as proof that the bond market caused the Nasdaq rebound. But Jonathan’s broader message is clear: from a technical perspective, he believes the recent low was meaningful and that the market’s momentum has turned bullish.

Our technology expert Luke Lango is reaching the same conclusion from a fundamental perspective.

Last week, Luke told his readers that he was watching for two things before getting aggressive with new AI infrastructure buys: confirmation from the hyperscalers that AI spending is strengthening, not merely continuing, and an end to the technical selling pressure whipsawing the group.

We’ve now gotten both.

Here’s Luke with what it means:

We’re doing something we have not done since the depths of the Iran War saga, and before that, the Liberation Day crisis back in April 2025.

We’re backing up the truck.

In Luke’s Early Stage Investor newsletter, he issued two new “Buys” on Monday. In Innovation Investor, he issued five. They’re all concentrated in AI infrastructure; the physical buildout of chips, power, cooling, and networking gear that the entire AI boom runs on.

Here’s Luke with more on his buying rationale:

A meaningful chunk of the recent weakness in AI infrastructure names was not about the businesses getting worse.

It was about one enormous, over-leveraged trader forced to sell stocks it still believed in, simply because it had borrowed too aggressively to hold them comfortably.

That risk is now gone.

To make sure we’re all on the same page, Luke is referring to Leopold Aschenbrenner, manager of the AI hedge fund Situational Awareness.

In recent weeks, as Aschenbrenner’s overleveraged AI bets came under pressure, leading to margin calls, he had to liquidate his entire $45 billion portfolio. This was a major contributor to the recent AI trade drawdown.

Luke believes the removal of that forced seller changes the near-term supply-and-demand picture for the entire group.

Back to Luke:

Markets tend to price in the fear of continued forced selling before it happens, which means some of the recent softness in our target names likely reflected worry about more Situational Awareness selling that will now never come.

Finally, Louis is looking at the market through the lens of investor positioning and sentiment.

He believes the forced selling didn’t merely pressure AI stocks – it may have produced the kind of capitulation that frequently marks an important market low.

From his Accelerated Profits issue yesterday:

The fund ultimately sold a large part of its public equity portfolio to Citadel. That fire sale was what pushed the NASDAQ to the edge of correction territory on Wednesday.

This action can be best described as “capitulation.”

The good news is that the Wednesday low may not need to be retested. Typically, capitulation selling does not have to be retested.

So, we can now look forward to what’s in store for us in August, and I think August will be a big rebound month.

Bottom line: three of our experts studied the same market, beginning in different places.

Jonathan with the charts… Luke with the AI fundamentals… and Louis with investor psychology.

But they all arrived at the same destination – this looks like a buying opportunity.

If you’ve been waiting on the sidelines for the dust to settle in the AI trade, all three are telling you that the opportunity may be here.

Have a good evening,

Jeff Remsburg

The post More Traders Predict a Fed Hike. Don’t Bet On It appeared first on InvestorPlace.

Since the Big Bang “banged” about 13.8 billion years ago, space itself has been expanding.

For decades, scientists thought that gravity would slow that expansion down. But observations through the Hubble Space Telescope in 1998 revealed the opposite.

The universe’s expansion is actually accelerating – about 5% to 9% faster than expected – and that’s forced astronomers to rethink the cosmos.

Today, the space economy appears to be entering its own period of rapid expansion.

Around a decade ago, the space industry was mostly viewed as government-funded rocket launches and scientific missions.

Think: The final years of NASA’s Space Shuttle program… government contracts awarded to traditional aerospace contractors, like The Boeing Co. (BA), and Lockheed Martin Corp. (LMT)… expensive rockets designed for one-way trips rather than commercial reuse.

Fast forward to today, and we just got our first real look inside the industry’s biggest company: Space Exploration Technologies Corp. (SPCX).

Elon Musk’s data-center-in-space enterprise reported its first-ever quarterly earnings report as a public company yesterday. And its earnings show that space is becoming more than a place for exploration…

It is an expanding, multibillion-dollar commercial industry.

Now think: Satellite internet. AI infrastructure. Communications. Defense. Data services.

So, the question for investors is no longer whether the industry will grow. It’s how to invest in a space economy that is expanding faster than many expected.

In today’s Smart Money, let’s take a look at SpaceX’s earnings. Then, we’ll explore where the biggest opportunities may emerge as this new space economy takes shape.

The Final Frontier Meets the Bottom Line

For the second quarter, SpaceX generated $7.8 billion in revenue, up about 92% year-over-year, and ahead of analyst estimates of $6.8 billion. The company is clearly becoming a real commercial business.

Its Starlink satellite internet service is generating recurring revenue, Falcon rockets are launching satellites, and SpaceX businesses across aviation, maritime, telecommunications, and defense are pouring money into space-based services.

Despite the strong revenue, the company still reported a net loss of $541 million, or 9 cents per share, due largely to AI data center expansion. SpaceX spent nearly $16 billion on AI infrastructure in the second quarter, pushing total capital expenditures (CapEx) to roughly $18.4 billion – far above what Wall Street expected.

This sent investor concerns into orbit and shares back to Earth. SPCX is down 8.6% today.

But the selloff was not about a lack of growth or demand for SpaceX’s services. The company was already down 15% from its $135 offer price heading into yesterday’s trading. Investors were pricing in massive AI spending concerns before the earnings report arrived. The report simply validated those concerns.

That puts SpaceX in the same issue facing just about all of Big Tech:

Is artificial intelligence generating enough revenue to justify the hundreds of billions they’re spending on data centers and other AI infrastructure?

Investors already believe in SpaceX’s vision. Now they want to know if it can generate enough cash to fund its ambitious AI and space plans.

The uncertainty isn’t demand; it’s valuation.

And that distinction is important. The market is not questioning whether the space economy will grow, but which companies will capture the profits.

That creates an opportunity in the companies supplying SpaceX.

And I’ve identified one company that sells the “picks and shovels” of the space economy, with products already operating in space today.

So, while SpaceX has to prove its massive spending can eventually pay off, this company simply has to keep selling more equipment into an expanding industry.

To SpaceX… and Beyond

Crucially, the company is not dependent on SpaceX’s success. (But if Starlink, AI infrastructure, and the Starship two-stage heavy-lift launch vehicle all succeed, suppliers across the space economy could benefit – including this one.)

Its customers include NASA, the European Space Agency, the U.S. military, and a growing roster of commercial space operators. These are same institutions that are driving the new space economy regardless of what any single rocket company does.

When you buy this stock, you are buying a front-row seat to several of the most consequential aerospace programs of the next decade through a companywith 50 years of combined flight experience and nearly 100 active customers.

And the company is expanding its reach into several new frontiers:

• A new contract with the U.S. Space Force.
• Quantum-secure satellites.
• The Golden Dome missile defense shield and more high-tech defense.
• The moon.
• The drone business.

But upon entering into this “final frontier,” I must warn you: The risks are real. The stock’s history of sharp swings tells you this is not a name for the faint of heart.

For the investor willing to accept those risks in exchange for exposure to the emerging space economy, however, this aerospace manufacturer offers real revenues, real contracts, and real hardware already in orbit. It is one of the very few publicly traded companies that can credibly claim all three.

Unlike SpaceX, it isn’t trying to build massive AI data centers or a global satellite internet network. Instead, its growth comes from winning contracts and making strategic acquisitions – not spending billions upfront and waiting light-years for a return.

It’s an overlooked opportunity in the growing space economy.

You can learn how to access the name of the space-based play by clicking here.

But, like I said above, the space economy is still expanding. That’s why I recommended another space-focused company on the opposite end of the spectrum. You can think of it as “space investing for chickens.”

Buried inside this very large, very profitable, very boring company is a robotics business with a direct connection to SpaceX. 

Click here to learn more.

Regards,

Eric Fry

Editor, Smart Money

The post SpaceX Revenue Jumped 92%, but This Supplier Could Be the Bigger Winner appeared first on InvestorPlace.

He had eaten a hamburger with raw Bermuda onion at the turn, walked off the course at Cherry Hills outside Denver with what he figured was a bad stomach, and went to bed. The chest pain woke him after midnight. The words “heart attack” emblazoned the newspaper headlines on a Saturday in September 1955, which gave the country a day and a half to sit with the news before the New York Stock Exchange opened.

The following Monday was a slaughter. 

The Dow Jones Industrial Average fell 6.5%, about $14 billion of value, the worst single session since the crash of 1929. And nothing about the American economy had changed over that weekend. The steel mills were still functioning, Detroit was still churning out vehicles, the baby boom kept booming. What had changed, however, was the story investors were telling themselves about the future…

The market regained its footing within weeks. The next bear market did not arrive until the spring of 1956. 

We just lived through our own version of that weekend. A single piece of writing about the situational awareness of AI models blew up the internet in late July, the AI infrastructure complex went into free fall, and some of the best growth stories in this market were cut in half or worse. 

Then the “medical bulletins” (read: earnings) came in. 

All four hyperscalers hiked capital expenditure guidance for 2026. All four gave bullish commentary on 2027. Amazon.com Inc. (AMZN) confirmed it on that Thursday, and the following session was the real back-up-the-truck moment.

We do not catch falling knives around here. We buy bouncing tennis balls. Right now the tennis balls are bouncing, and here are five of them we broke down on this week’s Being Exponential:

The Divergence

Before we get into the buy-the-dip names, let’s discuss the framework, because the framework is what you keep with you.

Every one of these stocks shows the same fingerprint. Forward 12-month earnings estimates go up and to the right in a clean, uninterrupted line while the share price nosedives. That divergence is fundamentally incongruent. Analysts who cover these companies are raising their numbers at the exact moment traders are dumping the shares, which tells you the selling is about sentiment rather than about the business.

The second tell is the 200-day moving average. Support that flips to resistance is a warning. A stock that keeps hitting its head on the same line in January, March, June, and July is a stock in a downtrend. The moment it knifes back through and holds, the character of the chart changes. That is the trigger. Divergence gives you the reason. The retake gives you the timing.

Palantir: The Tug-of-War Is Over

Palantir Technologies Inc. (PLTR) spent this year caught between SaaSmageddon fears and the reality of organic AI software growth. This quarter settled it emphatically.

Revenue grew 93% year over year, and more importantly grew 19% quarter over quarter. When you own a hypergrowth story, you want each three months better than the last three months. Commercial revenue rose 149% year over year and 28% sequentially, which answers the only real question anyone had about this company: how deep can Palantir push into cost-sensitive commercial buyers? Very deep, apparently. Net dollar retention of 157%. Adjusted operating margin of 62%. Free cash flow margin of 63%. A Rule of 40 score around 155%.

The knock has always been valuation. At roughly 60 times forward earnings, Palantir now trades near a two-year low multiple and within shouting distance of a five-year low, against growth I believe compounds above 50% into the end of the decade. I recommend buying this bounce, because the stock just retook the 200-day for the first time since January.

Caterpillar: The Industrial Fiber of the Buildout

Caterpillar Inc. (CAT) is the literal picks and shovels play. Prime power, backup power, the machines that move the earth a data center sits on. The buildout runs on Caterpillar iron.

Revenue rose 24% to $20.5 billion. Adjusted earnings per share jumped 73% because adjusted operating margin expanded 430 basis points to 21.9%. Free cash flow in the machinery, energy, and transportation business hit a record $5.1 billion. And the backlog climbed $9.4 billion sequentially to $72.1 billion, which means the numbers we saw this quarter are the numbers we see for the next several quarters.

Analysts model single-digit revenue growth for this year. I think that is far too low. At about 22 times forward earnings for a stable cash cow compounding earnings north of 25%, this one is priced like the buildout ends tomorrow. The chart already disagrees, because Caterpillar took a 26% drawdown, lost the 50-day and the 100-day, then V-shaped right back and reclaimed the 100-day as support.

Applied Optoelectronics and Fabrinet: the optics squeeze

AI clusters are bandwidth-hungry, and every incremental gigawatt of compute demands 800G and 1.6T transceivers, data center interconnect, silicon photonics, and eventually co-packaged optics.

Applied Optoelectronics Inc. (AAOI) is the highest-growth name I am aware of in optical networking at real scale, with triple-digit revenue growth expected this year and next and gross margins tracking from the low 30s toward the high 30s. It fell more than 65% from its July peak. It has already retaken the 200-day. That is the highest-torque expression of this theme.

Fabrinet (FN) is the quieter one. Fabrinet manufactures the hard stuff other people design, and that expertise is difficult to replicate. Call it 25% compounded revenue growth with thin gross margins that stay thin, which still delivers 30% earnings growth, at about 25 times forward estimates near a one-year low. Fabrinet reclaimed its 200-day this week and ended a run of lower highs and lower lows.

Nebius: The Wall Street 2K stock

Nebius Group N.V. (NBIS) exists because we are desperately short compute. Every hyperscaler launching more cloud capacity reinforces that, because scarcity gives every supplier of compute enormous pricing power.

Revenue is expected to leap from roughly $530 million in 2025 to $3.3 billion in 2026, then to nearly $11 billion, then toward $20 billion. Gross margin runs from about 41% this year toward 80% by the end of the decade. If you could build a stock in a video game, you would build this one. It trades near 13 times forward earnings. The stock dropped 40%, bounced clean off the 200-day, retook the 100-day, and is working on the 50-day.

The Window Is Open

This is the aggressive part of the cycle, and I say that with both hands on the wheel. The music is playing. We are in later innings, and later innings are where the big returns and the big mistakes both live.

Get the full breakdown, chart by chart, on this week’s episode of Being Exponential. Then join us later this week for our macro episode, where we tackle the situational awareness debate head-on.

In addition to the five buy-the-dip plays I mentioned today,  there’s one $15 stock that could soar over the coming weeks and months. Hint: It involves Elon Musk, AI, China… 

There will be a headline that spooks you. Similar stocks that drop for reasons that have nothing to do with the business underneath it. A moment where it looks, on the surface, like the story is falling apart.

That moment, if history is any guide, is exactly when the money that matters moves in.

The only question left is whether you’re positioned before that moment or after it. In fact, if you buy just one stock for the rest of the year, I urge you to make it this one. 

Click here to see what you’re missing.

The post 5 AI Infrastructure Stocks to Buy the Dip appeared first on InvestorPlace.

The second-quarter earnings season has turned into one of the strongest in years.

The S&P 500 is on pace for blended earnings growth of 47.4% for Q2. If that holds, it’ll be the best growth rate the index has posted since Q2 2021.

Just one week ago, that estimate sat at 38.0%. Two weeks before that, it was 23.2%. In other words, this number has nearly doubled in a month.

So, what’s driving it?

Mostly two companies – but not for the reason you’d think.

Real strength? Or the illusion of strength?

Alphabet, Inc. (GOOG) and Amazon.com, Inc. (AMZN) both posted eye-popping earnings surprises this quarter. But dig into the numbers, and you’ll find the “surprise” wasn’t really about search ads or Prime subscriptions.

Here’s FactSet on Amazon:

It is important to note that the (GAAP) EPS actual for Amazon.com for Q2 2026 included non-operating, pre-tax other income of $53.4 billion, primarily from investments in Anthropic.

However, as previously stated, the vast majority of analysts providing EPS estimates to FactSet used the (GAAP) actual EPS of $5.75 including the other income as the comparable number to their estimates.

Alphabet’s beat has a nearly identical story. Its own earnings release attributes $99.0 billion of its profit to unrealized and realized gains on equity securities – stakes in companies like Anthropic and SpaceX – which by itself boosted diluted EPS by $6.26. Strip that gain out, and Alphabet’s “beat” mostly disappears.

So, add Amazon’s $53.4 billion and Alphabet’s $99.0 billion together, and you get $152.4 billion in paper gains from the two companies’ investment portfolios – padding this quarter’s headline profit numbers before either company sold an extra ad or shipped an extra package.

But here’s the thing – these two companies are so large, and their paper gains so massive, that they’re not just inflating their own numbers – they’re pulling the entire S&P 500’s headline growth rate up right along with them.

Two stocks, out of 500, are a major driver of the index’s “best since 2021” story. And what happens if you remove Alphabet and Amazon entirely?

The blended earnings growth for the S&P 500 would fall from 47.4% to 28.8%.

That’s still a very good quarter. It’s just not a record-breaking one.

So, let’s dig deeper to see where the gains have been concentrating.

This sector is doing the heavy lifting

That gap – between the flashy 47.4% headline and the more grounded 28.8% reality – is exactly why it’s worth looking past the index-level number and asking a sharper question…

Beyond Big Tech, where has the strength been coming from?

Energy.

It’s posting the strongest year-over-year earnings growth of any sector in the index, at 135.3%. And these gains aren’t riding on one or two names.

Four of the sector’s five sub-industries are showing double-digit growth, led by Oil & Gas Refining & Marketing (277%) and Integrated Oil & Gas (172%).

But is now still a good time to be in oil? Aren’t prices in danger of crashing given the growing chatter around a new potential ceasefire deal with Iran?

On that note, this morning, Treasury Secretary Scott Bessent said that the U.S. and Iran could reach a deal to open the Strait of Hormuz today or tomorrow.

While the oil markets would certainly breathe a sigh of relief if that happens, it might matter less than many investors realize. You see, the real bottleneck right now isn’t crude – it’s refining.

Where the money is likely to keep flowing within the oil patch

Between disruptions in the Strait of Hormuz, Ukrainian strikes on Russian refineries, and China’s export ban, roughly 10% of global refining capacity is effectively offline. This is keeping fuel prices and refining margins elevated even as crude wobbles.

Here’s Bloomberg from last Friday, quoting ExxonMobil’s CFO:

“The constraint pain point in the energy system is refining,” ExxonMobil Chief Financial Officer Neil Hansen said in an interview.

It’s “something that perhaps the market isn’t fully focused on.”

Translation: even a ceasefire that cools crude prices may not bring fuel prices – or the refiners’ margins tied to them – down with it. Or at least not as fast as the market expects. So, this trade could have more life in it than the “oil is falling” headlines would have you believe.

This is part of why legendary investor Louis Navellier has put his Growth Investor subscribers into refiners.

From Louis’ latest issue:

Global oil refining margins recently breached another record high, as global refining capacity remains pinched due in part to restrictions on Russian diesel, limited shipping traffic in the Strait of Hormuz and Ukraine’s relentless attacks on Russian refineries.

As a result, many American refineries need to meet the ongoing demand for refined petroleum products like gasoline and jet fuel.

One refiner that both Louis and trading veteran Jonathan Rose of Masters in Trading: Live like is HF Sinclair Corporation (DINO).

While Jonathan has played DINO due to the crack spread, Louis has been attracted by the earnings strength.

On that note, the company’s refining segment alone earned $877 million, up from $166 million in the second quarter of 2025. HF Sinclair’s refinery gross margin also surged to $25.95 per produced barrel sold, representing a 57% year-over-year increase.

Louis recommended DINO at the end of June, and the official position is already up more than 30%. As I write, it trades under Louis’ “Buy Below” price of $100.

Another name that shows what “real” earnings growth looks like

DINO isn’t the only place Louis is finding real earnings strength – the kind that’s backed by an actual, growing business, not unrealized gains on an investment.

Across his Growth Investor Buy List, Louis has been watching the same pattern repeat all season. Here’s Louis:

Our Growth Investor stocks are characterized by 53.7% average annual sales growth and 112.4% average annual earnings growth.

Our stocks are also on track to post wave after wave of positive earnings surprises, as the analyst community has revised earnings estimates 16.8% higher in the past three months.

So far this earnings season, we’ve had 21 companies report results, and 18 have exceeded analysts’ earnings estimates. Our stocks have posted an average 31% earnings surprise.

Eighteen of 21. That’s a beat rate right in line with the record pace the broader market is putting up – except these beats are showing up in companies actually building the AI boom, not just holding stakes in it.

Take Celestica, Inc. (CLS), another one of Louis’ Growth Investor holdings.

It manufactures the servers, networking gear, and data center hardware that hyperscalers like Amazon, Microsoft, and Google need to actually run their AI workloads – the physical plumbing behind the AI boom, not the AI itself.

Louis just noted that last week, Celestica reported second-quarter revenue of $4.70 billion, up 62% year-over-year, with adjusted earnings per share of $2.54, up 83% from a year ago. Management also raised full-year guidance to $20.5 billion in revenue and $11.30 in adjusted earnings per share.

Once again, Celestica’s earnings weren’t goosed by an equity stake in a venture capital company. They came from the company selling more hardware, at better margins, because demand for AI infrastructure keeps outrunning supply.

Louis’ Growth Investor subscribers are up 84% in CLS as I write. But here again, you have room to get in. Louis’ “Buy Below” price is $409.

For all of Louis’ picks in Growth Investor, click here to learn about joining him.

Now, I just mentioned “an equity stake in a venture capital company” like it’s a bad thing. Of course, it’s not if you’re the one who owns the stake, and not if you got in early with the right person.

Which brings us to our next story…

The guy who keeps building things nobody saw coming – twice

Palmer Luckey built his first virtual reality headset out of spare parts and duct tape in his parents’ trailer, while homeschooled and still a teenager in Long Beach, California.

By 21, he’d sold that company, Oculus VR, to Facebook (now Meta Platforms (META)) for $2 billion.

Most people would call it a day and end up on a white sandy beach somewhere.

Instead, within a year of leaving Facebook, Luckey founded a defense company technology startup called Anduril, building autonomous drones and AI-piloted weapons systems for the Pentagon.

Today, private backers value Anduril at somewhere north of $60 billion.

One breakout company, built by a kid tinkering in a trailer, might be a matter of luck. Two breakout companies, in two completely unrelated industries, is skill.

But Luckey isn’t done…

He’s now working on a small nuclear energy startup called Valar Atomics. It builds compact reactors designed to sit directly behind data centers and supply them with power around the clock, a real bottleneck as AI’s electricity appetite outruns the grid.

In March, private investors valued Valar at $2 billion. As of two weeks ago, it’s already back in the market, talking to Sequoia about a new round – at a $6 billion valuation.

That’s a triple in about four months.

With this track record, would you be willing to bet on Luckey’s next company?

Of course. And it points toward a truth that every venture investor will tell you…

A great founder with a decent idea beats a great idea saddled with a mediocre founder, almost every time.

Why?

Simple – ideas get copied. Markets shift overnight. Competitors show up from nowhere. The one variable that adapts to all of that in real time is the person running the company.

That’s exactly why the first letter in Luke Lango’s PPT framework – People, Product, Timing – isn’t an afterthought. It’s the filter he runs before he looks at anything else.

Here’s Luke:

Getting through the door is not the same as making money.

The fact that a company is raising money does not make it a good investment. It makes it an opportunity to evaluate…

PPT starts with: Are the founders the kind of people who figure things out when everything goes wrong?

This question is exactly why a name like Luckey moves the needle before a single dollar of revenue shows up on a spreadsheet.

It’s also exactly the kind of filter that matters more in AI than almost anywhere else right now, given how many companies are raising money simply because they can, not because they should.

Luke dove deeper into this question and his broader PPT framework in last Thursday’s 2026 AI Megadeal Event. He walked through how he applies People, Product, and Timing to the private AI opportunities he’s tracking today – including one opportunity he believes could be a portfolio-maker.

As I covered in yesterday’s Digest, Luke gave it away during last week’s presentation. It’s a robotics startup offering a one-of-a-kind “robot school” platform that Luke considers the “ChatGPT moment” for artificially intelligent robots.

You can still watch the free replay right here, while it’s up.

As for Luckey, he’s not done with Valar Atomics either. He’s also founded Erebor Bank, a national digital bank tailored specifically for deep tech, defense, crypto, and hard science startups.

Keep your eye out for opportunities with people like Luckey. History shows that builders who win once rarely stop at once – and if you’re able to hitch yourself to them, the upside can be life-changing.

We’ll keep you updated on all these stories here in the Digest.

Have a good evening,

Jeff Remsburg

The post The $152 Billion Reason Earnings Look So Strong appeared first on InvestorPlace.

Today, Luke examines Apple’s acquisition of Q.ai – an obscure AI startup it reportedly purchased for nearly $2 billion despite having no sales or public product. He explains what that deal tells us about where the biggest AI gains can be made and shares the framework he uses to identify similar opportunities. He also applies that process in his free 2026 AI Megadeal Event, which you can watch here.

Here’s Luke with more…

*****************

“No f—ing way.”

That’s what Israeli venture capitalist Eden Shochat reportedly said after watching a YouTube video in 2009.

On-screen, a man moved in front of a camera while a digital skeleton mirrored every step and gesture in real time. Today, that might not sound remarkable – but in 2009, it looked like science fiction.

Source: YouTube

The company behind it was PrimeSense, an Israeli startup whose motion-sensing technology was later licensed for Microsoft Corp.’s (MSFT) Kinect gaming system. In 2013, Apple Inc. (AAPL) acquired PrimeSense for a reported $350 million and eventually used its depth-sensing expertise to support technologies such as Face ID.

Among PrimeSense’s founders was a young entrepreneur named Aviad Maizels.

After the acquisition, Maizels spent several years at Apple. Then he left and started another company.

This one was called Q.ai.

Founded in 2022 by Maizels, Yonatan Wexler, and Avi Barliya, Q.ai developed machine-learning systems designed to improve audio in difficult environments, understand whispered speech, and interpret subtle facial movements.

When Shochat’s team learned that Maizels was building something new, they asked to see it. They had been impressed by what he’d accomplished at PrimeSense and didn’t want to miss his next act.

Once again, the technology seemed almost too ambitious. This time, instead of watching from the sidelines, Shochat invested.

And in January 2026, Apple bought Q.ai for a reported $1.6 billion to nearly $2 billion. At the higher reported price, PitchBook estimates that the deal may have returned more than 30 times the original investment for some of Q.ai’s earliest backers — in roughly three years.

Q.ai reportedly had no sales and no publicly available product when Apple bought it. So it’s fair to ask: Why would one of the world’s largest companies pay nearly $2 billion for it?

And more importantly for us as investors: What did Q.ai’s early backers recognize before Apple came calling?

That’s what I want to show you today.

The answer reveals a different way to profit from the AI boom, one that doesn’t start by buying shares of Apple, Nvidia Corp. (NVDA), or another tech giant after the headlines hit. It starts much earlier.

And along the way, I’ll show you the three questions I use to evaluate every private AI company before I ever recommend it.

The Three Things Apple Was Really Buying

Apple hasn’t explained exactly how it plans to use Q.ai’s technology, but the broad appeal is easy to understand.

Computers have become extraordinarily powerful, yet communicating with them can still feel clumsy. Voice assistants mishear us. Background noise interferes. Devices struggle to understand whispers, facial movements, and other subtle signals people use naturally.

Q.ai is attempting to close that gap.

Its technology could become especially valuable as computing moves beyond keyboards and screens and deeper into AirPods, watches, glasses, phones, and other devices that remain close to us throughout the day.

But Apple wasn’t buying only a promising product.

It was buying three things:

The right people. A potentially valuable technology. And years of development time it could not afford to lose.

Those are the same three things I examine before considering an investment in any young private company. I call the framework PPT: People, Product, and Timing.

Let’s use that framework on Q.ai…

People: Start with Maizels. He had already built one technically ambitious company and sold it to Apple.

PrimeSense took technology that looked like science fiction and made it work in commercial products. Apple had employed Maizels, worked with his team, and incorporated the company’s expertise into its own devices.

Past success never guarantees another win, but Maizels had already shown that he could build advanced technology, turn it into something useful, and attract one of the most sophisticated buyers in the world.

That gave Q.ai’s early investors something more valuable than a polished pitch. It gave them evidence.

Product: Q.ai was working at the intersection of audio, imaging, and machine learning to help devices understand people more naturally. That matters because the next generation of computing may depend less on tapping screens and more on speaking, listening, watching, and interpreting context.

Q.ai is attempting to solve a problem that several of the world’s largest technology companies urgently want solved.

Timing: Apple is pushing AI across everything it produces. At the same time, it is competing with Meta Platforms Inc. (META), Alphabet Inc. (GOOG), OpenAI, and other device makers to shape the next major computing interface.

Apple could have spent years trying to reproduce Q.ai’s work internally. Instead, it bought the company that had already assembled the team and developed the technology. That is what favorable timing can do.

In other words, Apple was buying Q.ai’s people, its product, and the time those assets could save.

For Q.ai’s earliest investors, recognizing those three things before Apple did may have produced an extraordinary payday.

A Different Way to Invest in the AI Boom

Most investors participate in a buyout like this by owning the buyer.

They see Apple announce an acquisition and ask whether it will help Apple sell more iPhones, improve Siri, or compete more effectively in AI.

That can still be a profitable way to invest.

But Q.ai’s early investors occupied a very different position. They owned part of the company Apple wanted to buy.

They were already there when the acquisition was announced, when Q.ai was still an obscure young company attempting something difficult. By then, the opportunity was over.

That is the private-investing opportunity in plain English: Find valuable young companies before the tech giants decide they need them.

Big Tech has enormous amounts of money, but it does not have unlimited time. Apple, Google, Meta, Microsoft Corp. (MSFT), Amazon.com Inc. (AMZN), Anthropic, and OpenAI cannot invent every important AI capability internally.

When a smaller company develops technology that could save them years of work, buying that company may be faster and cheaper than starting from scratch.

That does not mean every promising AI startup becomes a multibillion-dollar acquisition. Some will run out of money. Others will build impressive technology but fail to turn it into a viable business.

That is why simply gaining access to these opportunities is not enough. You still need a disciplined way to decide which ones deserve your attention.

That’s what I designed PPT to provide. It helps me ask three practical questions:

• Have these People shown that they can execute?
• Does the Product solve a problem important customers urgently need solved?
• Is the Timing right? Is the market ready to reward the company now?

Q.ai appears to have answered yes to all three.

That is the work I recently took to Silicon Valley. I wanted to examine one specific private AI company from the inside. I wanted to study its founders, understand what its technology actually does, and determine why the timing could make it unusually valuable today.

I shared what I found during The 2026 AI Megadeal Event.

In that free presentation, I walk through the company using the same PPT framework we just applied to Q.ai. I explain who is building it, what problem its technology solves, why the opportunity exists now, and how individual investors can review the deal for themselves.

I cannot promise Apple or any other tech giant will buy this company. But I can show you why its People earned my attention, why its Product could matter, and why I believe the Timing makes it worth examining now.

Aviad Maizels built two companies that Apple ultimately wanted. Neither needed an IPO to generate a major payday for its earliest owners.

While plenty of the biggest winners in the next phase of AI will trade on the stock market, others will never reach that stage. They’ll be bought before Wall Street ever gets the chance to assign them a ticker.

The opportunity is to find them before a tech giant does.

Watch the replay of The 2026 AI Megadeal Event here.

Sincerely,

Luke Lango

Senior Investment Analyst, InvestorPlace

P.S. Luke has spent years studying the technologies that could define the next phase of the AI boom. What I like about his approach is that he digs into the founders, the product, and why the opportunity exists now. In The 2026 AI Megadeal Event, you can watch him apply that process to one private AI company he believes deserves attention today. I encourage you to check out the replay.

The post How to Find the Next AI Opportunity Before Apple Does appeared first on InvestorPlace.

Back when horizontal drilling and hydraulic fracturing were unlocking the biggest domestic energy boom in a generation, Albany, worried about water tables and quakes, outright banned the shale beneath the Southern Tier. The ban held and production in New York went to zero.

Everywhere else, it didn’t matter. Pennsylvania kept drilling. Texas kept drilling. Oklahoma kept drilling. The industry didn’t slow down, it transitioned to multi-well pads instead of single wells, water recycling instead of waste, smaller footprints doing more work.

New York, for what it’s worth, opted out of the boom and had to watch it happen from the sidelines.

I mention this because Albany just did it again. Governor Kathy Hochul signed an executive order in July banning new large-scale data centers across the state for up to a year, and more than a dozen other state legislatures have introduced bills aimed at the same target. Some of the loudest opposition, reporting suggests, is not even coming from New Yorkers. It is coming from social media accounts tied to foreign governments with an obvious interest in slowing America’s AI buildout down.

So here is the pattern again. A state says no. The capital doesn’t care. It builds where the door is open, and it builds smarter than it would have if nobody had pushed back at all. The bears keep pointing at bans and backlash as proof the AI Boom is losing steam. I keep pointing at the ledger.

Now the tape is starting to agree with the ledger again. Below, I team up with Louis Navellier to walk you through exactly what just changed, and why later innings just became my favorite time to buy:

When the Tape Lies: What the AI Infrastructure Sell-Off Really Means

Right now, Micron Technology, Inc. (MU) trades 30% below its high. SanDisk Corporation (SNDK) sits more than 50% off its peak. Celestica Inc. (CLS) fell 30% before its recent bounce. Corning Incorporated (GLW) slips below its 200-day moving average for the first time this cycle. As the charts break down, everyone keeps asking the same question: Is the AI Boom finally cracking?

Always check the ledger before you trust the tape. Corning posted core sales up 17%, earnings per share up 30% and Gen AI product sales that nearly double, with orders still accelerating. The four biggest AI spenders on earth – Amazon.com, Inc. (AMZN), Microsoft Corporation (MSFT), Alphabet Inc. (GOOGL) and Meta Platforms, Inc. (META) – all raised capital spending guidance this earnings season. None of them cut it.

Morgan Stanley raised its 2027 and 2028 hyperscaler capex forecast by 10%, to $1.2 trillion and $1.4 trillion. OpenAI lifted its projected compute spend through 2030 by 25%, to $750 billion. That is a boom outgrowing its own supply chain, quarter after quarter.

The Philadelphia Semiconductor Index fell 25% from its highs this summer, and the S&P 500 sits just 2% off its own highs. Compare that to early 2000, when that same 25% drop in semiconductors arrives alongside a 12% to 13% decline in the S&P, evidence of a crash spreading through the entire market. A localized sell-off that stays localized looks nothing like a localized sell-off that turns into contagion. This one stays contained, and that distinction matters more than almost anything else happening in markets right now.

In this episode of Being Exponential, Louis and I run through our favorite sectors for the back half of the year. We do not always agree on the individual names, but we agree completely on the setup: strong businesses, weak charts and a gap between the two that patient investors could exploit. Here is what we cover, sector by sector.

Semiconductors: Louis recommends Advanced Micro Devices, Inc. (AMD) and NVIDIA Corporation (NVDA) because both companies post strong sales and earnings forecasts, even after Nvidia’s recent deal with OpenAI briefly shakes the group. I recommend Corning. Corning is a builder of the optical backbone underneath the AI Boom, and a stock breaking its 200-day moving average the same week it reports numbers like that hands patient investors a mispriced opportunity.

Memory: Micron, Seagate Technology Holdings plc (STX) and SanDisk trade at single-digit forward earnings multiples on top of triple-digit revenue growth, with the current cycle not expected to peak until 2028 or 2029. That gives investors two to three years of runway before this cycle even reaches its top, and the stocks already price in a crash that has not happened. The AI memory shortage, driven by the sheer compute demands of AI labs racing each other, could persist for well more than a year.

AI infrastructure: This is where the tug-of-war shows up most clearly. Celestica, Vertiv Holdings Co (VRT), Quanta Services, Inc. (PWR) and Comfort Systems USA, Inc. (FIX) all report growing order backlogs, in some cases stretching to 2029, and all four still trade well below their highs. Part of the pressure comes from mechanics rather than business results: leveraged ETFs pile into the same names on the way up and unwind just as fast on the way down, and options market makers running mean-reversion programs against their own hedges add fuel to the fire. That combination looks a great deal like 1987, a market shock born of positioning, not profits.

Energy: The refining trade turns on regulation as much as oil prices. California’s decision to restrict diesel made from crude oil forces refiners like HF Sinclair Corporation (DINO) and Phillips 66 (PSX) to import refined fuel from South Korea and India rather than sourcing it domestically, tightening supply and lifting margins for the refiners left standing. On the power side, GE Vernova Inc. (GEV) posts a beat-and-raise quarter: revenue up 22%, orders up 88% and a backlog that expands $13 billion in a single quarter to $176 billion. That combination, rising revenue paired with expanding free cash flow guidance, defines a beat-and-raise quarter that actually matters.

Defense: Elbit Systems Ltd. (ESLT) builds missile defense systems now deployed across the Middle East, and Howmet Aerospace Inc. (HWM) continues to benefit from defense budgets that stay elevated. For diversified exposure, the iShares U.S. Aerospace & Defense ETF (ITA) and its European counterpart spread the bet across the sector rather than concentrating it in one name. One area worth avoiding: pure-play drone stocks. The long-term story around AI-powered drones makes sense on paper, but those stocks sit stuck below their 200-day moving averages and near 52-week lows, with no sign yet of the market rewarding the thesis.

Space: Space stocks carry real risk into August because SpaceX lockup expirations could unleash a fresh wave of insider selling, a wave that already pressures Rocket Lab USA, Inc. (RKLB), which loses its 200-day moving average for the first time since 2024. I remain a long-term believer in Rocket Lab because its acquisition strategy pushes the company toward becoming a vertically integrated space and compute business rather than a rocket launcher alone, but the next three to six months could bring more consolidation before that thesis plays out.

None of this argues for recklessness. The technical damage across AI infrastructure names is real, and a disciplined investor waits for the charts to confirm a bottom rather than guessing at one. But the ledger keeps saying the same thing the tape eventually has to agree with: capital spending accelerates, backlogs grow and earnings estimates keep rising into year-end.

That gap between the tape and the ledger is where the money gets made, the same gap that turned Black Monday into a forgotten line in the history books rather than the end of anything.

Watch the full episode of Being Exponential for the complete sector-by-sector breakdown, including where Louis and I disagree on timing and why that disagreement matters more than either of our individual picks.

The Bottom Line on AI Infrastructure Stocks

AI infrastructure stocks, the picks-and-shovels companies building the compute, power, and cooling behind the entire AI boom, just went through one of the sharpest sell-offs of this bull market.

Charts breaking. Headlines darkening. The usual chorus asking if the boom is finally over.

And in that very same window, the four biggest AI spenders on Earth, Amazon, Microsoft, Alphabet, and Meta, reported earnings and did the opposite of pulling back.

Every one of them raised their spending guidance. Combined, they’re now on pace to spend more than $700 billion building this out in 2026 alone.

The chart panicked. The business didn’t.

That gap, between what the ticker says and what’s actually happening inside the businesses, is where fortunes get made. It happened in 1987. It happened in 2000. It’s happening again right now, in the exact megatrend I’ve spent my career studying.

I’m telling you this because there’s one $15 stock that could go through the same thing. It involves Elon Musk, AI, China… 

There will be a headline that spooks you. Similar stocks that drop for reasons that have nothing to do with the business underneath it. A moment where it looks, on the surface, like the story is falling apart.

That moment, if history is any guide, is exactly when the money that matters moves in.

The only question left is whether you’re positioned before that moment or after it. In fact, if you buy just one stock for the rest of the year, I urge you to make it this one. 

Click here to see what you’re missing.

The post Luke Lango and Louis Navellier Rank the Best AI Stocks to Buy Right Now appeared first on InvestorPlace.

There was no single cause for the bearish turn.

Wall Street grew anxious about how quickly Big Tech could turn massive AI investments into profits. Reports that NVIDIA Corporation (NVDA) might backstop a large OpenAI data-center project revived “circular financing” concerns, while China’s fast-growing memory-chip industry raised new competition fears.

But then came last Wednesday’s Federal Reserve meeting (which I wrote about in Market 360 here).

The NASDAQ initially turned positive during Fed Chair Kevin Warsh’s press conference. But the rally abruptly reversed as Treasury yields surged, sending already-nervous investors rushing for the exits.

It looked like a capitulation day – the kind of washout that can finally exhaust the sellers and clear the way for strong stocks to bounce.

And that appears to be what’s happening.

For example, Microsoft Corporation (MSFT) has repeatedly said that limited capacity has prevented Azure, its cloud computing business, from meeting the demand it is seeing.

For a long time, Wall Street seemed to ignore those comments. They remained focused on the bill for all those data centers.

But when Microsoft announced earnings after the bell on Wednesday, the verdict was clear. Azure revenue surged 43% year over year in its latest quarter, while the cloud segment surpassed $100 billion in annual revenue for the first time.

The stock is up nearly 25% since Wednesday’s close.

In other words, this is not a “Field of Dreams” moment where Big Tech thinks it can “build it, and they will come.”

The customers are already there.

As Rob Spivey, Director of Research at our corporate partner Altimetry, explained in this week’s episode of Navellier Market Buzz, these companies are essentially scrambling to finish building the stadium while a crowd waits outside to get in.

Rob and I discussed the recent semiconductor rout, Wednesday’s capitulation day and why he believes the volatility has created new buying opportunities.

In fact, he identified two companies that could benefit as the AI infrastructure buildout continues.

Click the image below to watch the latest episode of Navellier Market Buzz.

If you haven’t already, click here to subscribe to my YouTube channel. Plus, if you’d like to learn more about Rob, click here.

Looking Beyond Today’s AI Leaders

Rob’s two recommendations make it clear: The AI boom is no longer benefiting chipmakers alone.

As companies race to build more data centers, they also need power generation, natural gas infrastructure, cooling systems, construction equipment and countless other products and services.

That creates opportunities in parts of the market that many investors may not immediately associate with artificial intelligence.

And this is just the beginning, folks.

The current AI infrastructure boom is being built around technologies like ChatGPT, Claude, Gemini and Grok. But behind the scenes, the U.S. government is preparing an even more ambitious project that could dramatically accelerate the pace of scientific discovery.

I call it the AI Reset of 2026.

This project is designed to connect some of America’s most powerful supercomputers into a massive new AI system capable of tackling complex scientific challenges in medicine, energy, quantum computing and other fields.

And just as today’s data-center boom is creating winners beyond the semiconductor sector, this next phase could produce an entirely new class of AI investments.

My research team and I have identified several companies positioned to help build and power this system.

Click here to learn more now.

Sincerely,

Louis Navellier

Editor, Market 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

NVIDIA Corporation (NVDA)

The post The AI Boom’s Next 2 Winners May Surprise You appeared first on InvestorPlace.

In 1977, a semi-retired chip executive named Mike Markkula met two kids running a computer company out of a garage.

He liked what he saw enough to write a $250,000 check – cash and a loan guarantee combined – for a one-third stake in the business.

That company eventually became Apple (AAPL).

When Apple rang the opening bell on its first day as a public company in December 1980, Markkula’s shares were worth $203 million.

In 2004, a hedge fund manager named Peter Thiel wrote a $500,000 check to a Harvard dropout’s fledgling website. It was called “The Facebook” back then. Thiel’s money bought him a stake in a company valued at just $5 million.

Today? Meta Platforms (META) is worth about $1.4 trillion.

Run the numbers, and Thiel’s stake grew more than 280,000-fold. His eventual stock sales cleared north of $1 billion – making that half-million-dollar check one of the most lucrative angel investments in Silicon Valley history.

Then there’s Chris Sacca. In the late 2000s, his tiny venture fund, Lowercase Capital, invested $300,000 into a scrappy ride-hailing startup’s angel round – something called Uber (UBER).

By the time Uber went public in 2019, that early bet – combined with additional money Sacca put in later – was estimated to be worth more than $2 billion.

Three completely different industries, three completely different eras – but the same underlying story: a small, early check into the right company at the right moment can turn into a fortune.

So, how do you find your own story?

The door is no longer closed

Thiel, Markkula, and Sacca weren’t just early. They were insiders – the kind of people who got a seat at the table long before any of those companies ever considered going public.

For most of the last century, that’s exactly what kept everyday investors out of stories like these. Getting into a private company before its IPO meant you needed a venture fund behind you, serious money of your own, or the right people in your contacts list.

Recent changes to securities law have opened that door. But showing up isn’t the hard part anymore – knowing how to find the right opportunity is.

Private companies aren’t like public stocks. They’re younger, less public about their information, and carry a real risk of going to zero. That’s the gap tech expert Luke Lango recently built a private-investing framework to close. He walked through it live, step by step, last Thursday.

And it couldn’t come at a better time…

AI is moving fast enough to create a wave of potential 100X opportunities – the kind most investors won’t recognize until they’re already priced in.

Consider “physical AI” – something that Luke recently wrote about. These are the systems that let robots do real work in the real world, not just answer questions in a chat window.

Here’s Luke:

I think the next bottleneck is forming in robotics.

A language model can train on text because the text already exists, scattered across the internet, free for the scraping. A robot learning to fold laundry or bus a table has no equivalent shortcut.

Every skill must be demonstrated physically, recorded, and labeled one motion at a time, and that process remains slow and genuinely expensive even as the tools around it improve.

That bottleneck – teaching machines to function in physical space instead of just text – is exactly the kind of obstacle Luke built his framework to spot.

It makes sense. Invest in the company that clears a critical bottleneck, and you’re positioned for a windfall when the rest of the market comes rushing for your solution.

Back to Luke:

Those are exactly the kinds of AI businesses I want to investigate as private investment opportunities.

They’re solving a problem that I believe customers will become increasingly desperate to solve.

Luke unpacked this during last week’s 2026 AI Megadeal Event. He also gave away the name of a robotics startup that counts Nvidia (NVDA), Microsoft (MSFT), Salesforce (CRM), and the Mayo Clinic among its clients.

Here’s Luke:

Its one-of-a-kind “robot school” platform is rolling out now and I consider this to be the “ChatGPT moment” for artificially-intelligent robots.

I project this startup’s revenues could balloon from $18 million at the end of this year to as high as $360 billion by 2029.

But physical AI is just one bottleneck. AI is creating many more – and Luke built his framework specifically to spot them before the rest of the market catches on.

To learn more, you can catch a free replay of last Thursday’s presentation right here while it’s still available.

More on these opportunities later this week.

AI is becoming dirt cheap – and changing the investment math

Last Thursday, OpenAI did something that most investors missed – but it’s critical you know what happened.

It cut its AI software prices by up to 80%.

Here’s CNBC:

The company is facing pressure to cater to a more cost-sensitive customer base, where enterprises have been less inclined to deploy expensive models without a clear picture of the return on their investments. 

AI software is becoming dirt cheap – and it’s happening at a breakneck pace. In last Friday’s issue of Investing Insider, I looked at this.

Consider this statistic from the issue…

Between November 2022 and October 2024, the cost of running an AI model with roughly GPT-3.5-level performance plunged from $20 to just $0.07 (per million tokens).

That’s a decline of more than 99.6% – or a 280-fold reduction – in less than two years. Stanford University reports that, depending on the task, AI inference prices have been falling by anywhere from ninefold to 900-fold per year.

OpenAI isn’t the only company driving costs lower. As our macro investing expert Eric Fry of Fry’s Investment Report noted last week, Chinese developers continue releasing increasingly capable AI models at dramatically lower prices.

Here’s Eric:

China’s progress shows that AI competition may become less about who builds the best model and more about who builds models that are “good enough” for most users.

That’s an important shift.

The AI race is no longer just about building the smartest model. Increasingly, it’s about building one that’s “good enough” at the lowest possible cost.

Now, this is a double-edged sword. While inexpensive AI could unleash an explosion in AI adoption, it also creates a brutal arithmetic problem.

If the price of intelligence falls 99% – as we just saw that it has done – demand must rise more than 100-fold merely to preserve the same amount of industry revenue.

For consumers, cheaper AI is unquestionably good news. But for investors, this cost crush requires us to evaluate our portfolio holdings with a new question:

Does this company benefit because AI is expensive…or because AI becomes ubiquitous?

The market is beginning to ask that question

Think about GPU rental companies.

Their business flourished because customers were willing to pay premium prices for scarce AI computing capacity. But as AI models become cheaper and more efficient – and as more computing capacity comes online – the premium attached to that scarcity could begin shrinking.

CoreWeave (CRWV) illustrates this debate.

As you can see below, since early May, the stock has fallen by more than 40% as investors have begun to question whether today’s premium AI infrastructure economics can last indefinitely.

The concern ties into our new evaluation question: If intelligence becomes dramatically cheaper, companies that rely on premium-priced AI compute may eventually face pricing pressure.

Of course, CoreWeave bulls see the story very differently. They argue that falling prices won’t matter if AI usage explodes even faster.

To their point, history is full of technologies whose prices collapsed while demand grew so rapidly that the industry’s biggest winners continued thriving.

But this usage/price escalator is the issue for many AI companies today.

I’ve used an analogy in recent Digests to explain this dynamic…

Imagine you’re climbing a descending escalator. Your upward climb represents exploding AI usage. The downward-moving escalator represents rapidly falling AI prices.

As long as you climb faster than the escalator descends, you still make net progress toward the top. In other words, total spending on AI compute continues rising – even if each individual AI query costs much less.

That’s CRWV’s bullish case. But if the escalator ever begins moving down faster than you can climb, the economics change.

Eric is zeroing in on this same “cost” issue but from a different direction

Writing about China’s rapidly improving AI ecosystem at significantly lower cost, he concludes:

We should pay closer attention to how quickly the competitive landscape is changing…

China continues to prove that the next phase of the AI race may be defined by efficiency, and who can achieve the most with the resources available.

To see where Eric believes investors should be positioned as AI becomes cheaper, more efficient, and increasingly “good enough,” click here to learn more about Fry’s Investment Report.

Bottom line: AI costs are crashing. The question now is whether AI adoption can keep climbing faster than prices keep falling.

So, keep this question in mind as you look at your current holdings and evaluate new ones:

Does this company benefit because AI is expensive…or because AI becomes ubiquitous?

One unexpected beneficiary of cheap AI

We just looked at falling AI costs from the perspective of investors. But let’s step back and think about falling AI costs from consumers’ perspective.

If intelligence becomes dramatically cheaper, we should all be able to accomplish more in less time. AI will increasingly handle routine tasks, summarize information, automate busywork, and free us to spend more time doing things we enjoy.

That doesn’t just change the technology industry. It changes how we spend our lives.

Senior analyst Brian Hunt, editor of Money & Megatrends, believes that’s creating an overlooked investment opportunity.

Here’s Brian:

As technological innovations such as AI programs and robots perform more “basic” tasks, people will have more time for leisure, entertainment, and wellness.

The more time we spend interacting with AI, the more we’ll crave experiences that no algorithm can replicate.

Brian calls these “real world experience” businesses – companies that benefit when people spend less time behind screens and more time living. And in last Thursday’s issue, he gave away seven of them.

Three names from his list resonated with me…

Vail Resorts (MTN)

Vail owns many of North America’s premier ski resorts, including Vail, Beaver Creek, Breckenridge, Park City, and Whistler Blackcomb. Brian believes destination travel and outdoor recreation stand to benefit as AI gives people more time to spend away from their screens.

VICI Properties (VICI)

VICI owns many of America’s premier entertainment destinations, including Caesars Palace, MGM Grand, The Venetian, and Mandalay Bay. It’s also expanding into wellness resorts and family entertainment, giving investors broad exposure to the growing demand for real-world experiences.

Live Nation Entertainment (LYV)

Live Nation is the world’s largest live entertainment company, promoting concerts, operating venues, and selling tickets through Ticketmaster. If consumers increasingly value experiences over digital consumption, live events could remain a powerful long-term growth story.

Here’s Brian’s bottom line:

Over the next 10 years, AI and robotics will take on many of the jobs and tasks humans perform now. This will free up our time to pursue leisure, entertainment, and wellness interests.

This trend will benefit the “real world experience” businesses detailed above.

To see his full list of companies positioned to benefit as AI gives us more time to spend in the real world, click here to learn more about joining him in Money & Megatrends.

Brian publishes every day the market is open, spotlighting and tracking opportunities like this. One of my favorite parts of these issues is that Brian gives away – totally free – loads of stocks positioned to benefit from his analysis.

Just click here to sign up.  

We’ll keep tracking all these stories here in the Digest.

Have a good evening,

Jeff Remsburg

The post AI Prices Just Fell 280-Fold – Now What? appeared first on InvestorPlace.

Today, I’ve asked my colleague Luke Lango to share that story.

But instead of second-guessing famous venture capitalists, he’s interested in a more useful question: Why did some experienced investors walk away from Google while others recognized its potential?

Luke believes the answer still matters today. Below, he breaks down the simple framework he uses to evaluate young companies before they become household names. Then, if you’d like to see that process applied to a real private AI opportunity, you can watch the replay of his free 2026 AI Megadeal Event.

Take it away, Luke…

Every great investor has a list they would rather nobody ever saw.

Not their biggest winners, of course. They’re happy to brag about those.

It’s the list of their biggest misses.

Companies they looked at… considered… sometimes even met with… and decided to pass on.

For most investors, those missed opportunities disappear into history.

But some venture capital firms do something you wouldn’t expect.

They publish them.

Bessemer Venture Partners calls it its “Anti-Portfolio”—a running list of billion-dollar companies it had the chance to invest in but didn’t. Apple. Tesla. Airbnb. PayPal. Google.

One of those misses came after partner David Cowan refused to visit a garage where two Stanford students wanted to show him a new search engine.

Those students were Larry Page and Sergey Brin. The search engine was Google.

What did the investors who said “yes” see that everyone else missed? That’s what I want to explore today.

Because the same clues that convinced a handful of investors to back Google before almost anyone had heard of it can still help us evaluate young companies today. And they’re the same three questions I ask before I ever recommend a private investment.

Cowan wasn’t alone. Another company looked at Google, studied its technology, negotiated a purchase price… and still decided to pass.

Why Excite Walked Away From Google

In 1999, Excite was one of the internet’s leading search and web-portal companies. According to venture capitalist Vinod Khosla, Larry Page and Sergey Brin were willing to sell Google to Excite for about $1 million. Khosla even helped negotiate the price down to roughly $750,000.

Still, Excite passed.

Former Excite CEO George Bell later explained why. Google wanted Excite to replace its existing search engine with Google’s technology. After testing it, Excite decided the improvement wasn’t dramatic enough to justify ripping out years of engineering work.

Whether that was the only reason is still debated. Some observers have argued Google’s search results were actually too good, sending users quickly to other websites when Excite’s business depended on keeping people on its own pages.

Either way, the lesson is the same. Excite evaluated Google based on the business it already had, but Page and Brin were trying to build the business the internet was about to need.

That’s an easy distinction to see today, but it wasn’t anything close to clear in 1999.

Fortunately for the two founders, not everyone viewed Google through the same lens.

In August 1998, Sun Microsystems co-founder Andy Bechtolsheim wrote them a $100,000 check before Google had even been formally incorporated. That investment helped move them from their Stanford dorm rooms into the very garage David Cowan was trying to avoid.

The following year, Sequoia Capital and Kleiner Perkins invested another $25 million.

According to Kleiner Perkins, Page and Brin showed up to their pitch meeting with a 17-page presentation containing only two pages of financial projections. Google didn’t have a proven business model. It didn’t even have a complete management team.

But it had something the investors believed mattered more:

• Great founders.
• A product people overwhelmingly preferred.
• And demand that was growing faster than almost anyone appreciated.

Google’s search traffic was reportedly increasing about 50% every month through word of mouth alone. Stanford’s own computer network struggled to keep up.

Looking back, the investors who backed Google saw three things they believed mattered most: the people building the company, the product they had created, and the timing of the opportunity.

Today, I call that framework People, Product, and Timing—or PPT.

It’s the same approach I use whenever I evaluate a private company, and Google remains one of the clearest examples of why those three questions matter.

Why This Matters Today

Google’s earliest investors had very little to work with.

There was no established business model. Very little financial history. No Wall Street analyst reports. No quarterly earnings calls.

They had to make a judgment based on the founders, the product, and where they believed the market was heading.

That’s still the job.

Today, more private companies are raising money from everyday investors than at any point in modern history. That creates opportunities previous generations simply didn’t have. But it also requires a thoughtful way to separate the handful of exceptional businesses from the thousands that never find their footing.

That’s why I built the People, Product, Timing framework.

It’s the process I use before I recommend any private investment, and it’s the same process I recently applied to one AI company during my 2026 AI Megadeal Event.

In that presentation, I explain who built the company, what it has created, why I believe the timing is attractive, how the investment works, and the risks every prospective investor should understand before making a decision.

If you’ve ever wondered how professional venture capitalists evaluate young companies years before they reach the stock market, I think you’ll find the presentation worthwhile.

I hope you’ll join me.

Watch the replay of The 2026 AI Megadeal Event here.

Sincerely,

Luke Lango

Senior Investment Analyst, InvestorPlace

P.S. One of the reasons I enjoy reading Luke’s work is that he rarely asks readers to accept a conclusion without seeing the reasoning behind it. During The 2026 AI Megadeal Event, he walks through his People, Product, Timing framework step by step and applies it to a real private AI company. Whether you ultimately invest or not, you’ll come away with a better understanding of how experienced venture investors think about opportunities long before a company has a ticker symbol.

The post How to Think Like the Investors Who Bought Google Early appeared first on InvestorPlace.

This Week’s Ratings Changes:

Upgraded: Strong to Very Strong

Downgraded: Very Strong to Strong

Upgraded: Neutral to Strong

Downgraded: Strong to Neutral

Upgraded: Weak to Neutral

Downgraded: Neutral to Weak

Upgraded: Very Weak to Weak

Downgraded: Weak to Very Weak

To stay on top of my latest stock ratings, plug your holdings into Stock Grader, my proprietary stock screening tool. But, you must be a subscriber to one of my premium services.

To learn more about my premium service, Growth Investor, and get my latest picks, go here. Or, if you are a member of one of my premium services, you can go here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Berkshire Hathaway Upgraded, Carvana Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

Two months later, his next company fit inside his living room.

The polished Silicon Valley campus and executive staff would come later. Hoffman already had the relationships and credibility to spend the rest of his career writing checks into other people’s companies.

Instead, he started LinkedIn.

It was his second attempt to solve a problem that had already beaten him once.

How SocialNet’s Failure Shaped LinkedIn

Five years before LinkedIn, Hoffman founded SocialNet, one of the earliest attempts to build an online social network.

Social networking barely existed as a category. Nearly everything – the product, the user behavior, the business model – was unproven.

You could explain the failure with two easy words: too early.

The market probably was. But Hoffman has never hidden behind that excuse.

He has said SocialNet spent too long trying to launch a perfect product. Instead of getting it in front of users and learning quickly, the team worked from a rigid idea of what people wanted.

That delay created another problem. SocialNet never attracted enough users to tell whether the product was wrong or the company simply was not getting it in front of enough people.

The feedback Hoffman needed most was the feedback SocialNet never gave itself enough time to hear.

Hiring compounded the problem. Hoffman favored people who had succeeded in stable roles. SocialNet needed adaptable operators who could change direction as the market revealed itself – what he later called “learners.”

The investor fit was no better. As the company struggled, Hoffman wanted to adjust based on what the team was learning. His backers pushed for television advertising.

That disagreement helped push him out the door and into PayPal.

SocialNet failed. The lessons followed him.

What Reid Hoffman Changed When He Built LinkedIn

At PayPal, Hoffman served as executive vice president, running point on partnerships and the company’s external relationships.

He saw firsthand how regulation, competition, and fundraising pressure collide when a new financial network starts to scale. Then he helped take PayPal public and steer it through the sale to eBay (EBAY).

Most people would have viewed that acquisition as the finish line. Hoffman treated it as preparation.

When he started LinkedIn, he did not return to the same playbook and hope for a better result. He carried forward specific lessons about product development, distribution, hiring, and investors.

He brought people with him, too.

LinkedIn’s founding group included colleagues from both SocialNet and PayPal. They had already watched Hoffman operate under pressure and still chose to bet on him again – an advantage no first-time founder can buy.

LinkedIn also began with a sharper purpose: build a network around professional identity and opportunity. And this time, Hoffman launched before everything felt finished.

In May 2003, he invited roughly 350 contacts to create profiles. By the end of that month, LinkedIn had about 4,500 members.

The product, business model, and leadership all changed. The network kept growing.

And in 2016, Microsoft (MSFT) agreed to acquire LinkedIn for $26.2 billion.

A failed social network had not disqualified Hoffman from building another one.

It had prepared him.

The Second-Act Founder Advantage

The best second-act founders have already lived through mistakes that first-time founders have yet to encounter.

They know how quickly a startup can burn through cash, how easily a strong product can stall without distribution, and which early hires can keep moving when the plan breaks.

Many return with trusted employees, customer relationships, investors, and a reputation that helps them recruit faster.

That can cut years from the learning curve.

But pedigree can also become a trap.

A prior exit can create overconfidence. Investors may excuse weak evidence because the founder succeeded once before. And a famous name can push the valuation higher before the new company has earned it.

Past success should sharpen the questions we ask, not answer them.

Selling one company can open the next door. It does not tell you whether the founder deserves another check.

Conviction comes from a founder who can name the mistakes, show how those lessons reshaped the new company, and convince great people to follow them back into the arena. 

Nearly a quarter-century after launching LinkedIn from his living room, Hoffman is stepping back into that arena himself. This summer, he announced plans to leave Microsoft’s board and devote more attention to Manas AI, an AI-native drug-discovery company he co-founded.

After SocialNet, PayPal, LinkedIn, years of venture investing, and nearly a decade on Microsoft’s board, Hoffman is still building.

For some founders, an exit is permission to stop.

For the most ambitious, it’s a chance to attempt something harder.

Four Questions to Ask Before Backing a Repeat Founder

An exit gives a founder money and credibility. What I care about more is what they learned – and who is willing to build with them again.

Hoffman brought both into LinkedIn: the mistakes of SocialNet, the scaling lessons of PayPal, and colleagues who had already seen him under pressure.

That is the test. Which mistake changed the way the founder operates? Who followed them into the next company? What changed in the market? And why start again when investing, advising, or retiring would be easier?

The answers reveal whether the second act carries a genuine edge – or whether investors are simply paying a premium for yesterday’s success.

The Next Second Act Is Already Underway

By the time one of these companies reaches the public market, the founder’s story is usually obvious.

The prior win is in the bio. The marquee investors are in the prospectus. The early employees are seasoned executives. And Wall Street has packaged the whole thing into a clean narrative.

Off-market investing forces you to make that call much earlier – while the company is still taking shape and the outcome remains deeply uncertain.

Recognizing the name is easy. Figuring out whether the founder turned experience into an edge is the real work.

How I Apply the Repeat-Founder Test

That is the lens I applied to one specific opportunity at The 2026 AI Megadeal Event.

I walked through the founders’ backgrounds, the lessons they carried forward, what they are building now, why the market may be ready, and what could still go wrong.

Then I revealed the full recommendation, completely free.

The opportunity is still open today. But its capacity is finite. Once the deal fills or the deadline arrives, it is gone.

That does not make it a good investment by itself.

Scarcity cannot rescue a weak company. Even an experienced founder cannot make a bad price attractive. And no previous success can guarantee another one.

Still, a founder who learned from failure, kept the trust of talented people, and came back for a bigger problem starts with advantages a first-time entrepreneur may need years to build.

Reid Hoffman did not build LinkedIn because PayPal made him infallible.

SocialNet taught him where he was wrong. PayPal taught him how to scale a network under pressure. And people who knew him well chose to follow him back into that living room.

That is the second-act advantage.

The first exit earns the founder an audience. The next company still has to earn your capital.

Watch the free replay of The 2026 AI Megadeal Event now.

The post LinkedIn’s Founder Is Going Back Into Startup Mode appeared first on InvestorPlace.

Imagine you own a small, successful restaurant chain. A couple of neighborhood locations with dedicated fans and decent lines that are never too long or too short. Life is great.

Then, your whole town decides your business is worth $250 million… and hands you $15 million to go prove it.

That’s probably why Elon Musk seems so frazzled in recent interviews. The world’s richest man was essentially given the same mandate by investors in Space Exploration Technologies Corp. (SPCX), scaled many times larger.

The mammoth initial public offering raised $85 billion in cash for his company… and investors are now demanding that the company be worth somewhere north of $1.5 trillion.

To fulfill that promise, Musk is implementing a familiar Big Tech tactic: Use acquisitions to juice internal growth. In early June, SEC filings revealed Musk had personally spent at least $1 billion to buy APR Energy, a company focused on powering AI data centers. Then on June 16, SpaceX bought AI coding platform Cursor for $60 billion – a roughly 100% premium to that startup’s last private valuation.

SpaceX will continue snapping up companies… and many will be public firms investors like you can buy before it happens. I will discuss the seven most likely publicly traded candidates below.

Of course, others will be privately owned, like Cursor was. InvestorPlace Senior Analyst Luke Lango can help you get in on these earlier-stage deals. In a new free presentation, The 2026 Megadeal Event, he lays out his method for spotting these targets and step-by-step instructions for buying them before everyone else gets in.

Click here to watch that free presentation.

And now, the seven public companies I think SpaceX has in its acquisition crosshairs.

Tier 1: “I’d Be Surprised If They Don’t Happen”

Tesla Inc. (TSLA): The most obvious SpaceX acquisition is more of a family reunion. On July 22, Elon Musk told investors on Tesla’s earnings call that “there’s more and more overlap” between his two companies. Betting markets are giving a 64% chance of an acquisition by the end of 2027, while some analysts say the chance could be as high as 90%.

The rationale is straightforward: A SPCX-TSLA merger would consolidate Musk’s technology empire. Tesla could supply batteries and manufacturing expertise to SpaceX’s satellites and AI infrastructure, while Starlink could provide connectivity for Tesla vehicles and humanoid robots. Most importantly, the two firms can reduce double-spending on AI research. Both companies are currently pursuing expensive AI projects (Tesla’s Robotaxis, xAI’s large language models), and putting them under one roof would give them better access to computing power and talent.

A deal would also benefit Tesla shareholders, because Musk only controls around 20% of voting shares at the electric vehicle maker (vs. 80%-85% at SpaceX). He would have to offer a relatively hefty premium to Tesla’s shareholders – probably between $420 (ha!) and $500 per share – because Tesla shareholders would be losing both future upside and voting power at the new entity. (Musk can then unilaterally approve the deal at SpaceX.) Of course, Tesla remains a risky bet that I still avoid, but the possibility of a SpaceX takeover should stop anyone from betting against this stock.

EchoStar Corp. (ECHO): In September 2025, this telecom and satellite company negotiated a deal with SpaceX to exchange some of its satellite spectrum for SpaceX stock. Think of satellite spectrum like an FM radio frequency; a company must “own” a channel to use it. EchoStar had plenty of unused spectrum through Dish Network, and SpaceX needed it for Starlink. SpaceX paid with a mix of cash and its own stock and bought even more two months later.

Now, those same SpaceX shares are worth over $30 billion, or almost two-thirds of EchoStar’s entire enterprise value – the company’s market value plus its debt.

That makes EchoStar an unusually attractive acquisition target for SpaceX. With a little bit of financial wizardry, SpaceX can effectively buy back those old shares using new shares and receive EchoStar’s remaining business for just $17 billion. This all-stock swap transaction would give SpaceX valuable assets worth roughly $32 billion, and include goodies like Boost Mobile, Dish TV, HughesNet, Sling TV, unused spectrum, and more.

In addition, 90% of EchoStar’s voting shares are owned by its founder, Charlie Ergen, who is now 73. His recent sales of spectrum to SpaceX – and a separate $23 billion deal with AT&T Inc. (T) – are a classic sign of a founder-owner getting ready to retire. I give it at least a 50% chance that EchoStar prepares itself for sale within a year.

Tier 2: The Strategically Obvious

Anterix Inc. (ATEX): America’s “spectrum landlord” hired Morgan Stanley in early 2025 to begin a strategic review after fielding takeover interest. The company holds the country’s largest portfolio of licensed 900-megahertz (MHz) spectrum – the airwaves used for land-based networks (think cellphone towers).

And if SpaceX can lay its hands on all this bandwidth, it would gain the ground-level frequencies it needs to beam Starlink service straight to everyday devices. No dish or special antenna required.

Conveniently, Morgan Stanley is also the primary bank involved in financing Tesla and SpaceX. An acquisition could be negotiated in a swivel chair.

Now, Anterix is a less likely candidate for acquisition than EchoStar because some of its spectrum is already used by local utilities and telecom firms. Regulators might also balk at giving SpaceX so much bandwidth. So, it is not as “clean” a purchase. But Anterix’s relatively low price and vast spectrum holdings make it something SpaceX might be willing to fight for. I give it a 1-in-3 chance that SpaceX makes a bid by the end of 2027.

GitLab Inc. (GTLB): Now, here is a company I would recommend for buy-and-hold investors.

GitLab is a firm that helps its customers build and manage software. And it is an unusually well-suited target for SpaceX because Musk’s company already owns the other pieces.

Think of the software business like a textbook publishing company. There might be dozens of authors, editors, and quality-control analysts. Then there’s book printing, distribution, and follow-up for the next edition. After all, no textbook is perfect the first time around.

SpaceX already has the first parts nailed down. Grok Build is a coding engine, and Cursor is a developer workspace. It also has Colossus, the giant AI supercomputer that acts like the printing press that churns out finished work at an industrial scale.

What’s missing is everything that happens in between. Someone has to check each chapter for errors, get the book out the door, track which copies are in circulation, and manage the corrections that inevitably pile up for the second edition.

In software, that’s GitLab’s job. The company’s platform does the unglamorous back-office work that turns a pile of coding “manuscripts” into a publishing business. It is also already FedRAMP compliant (the gold standard for the government and its contractors), which fits in well with SpaceX’s U.S. government work.

In addition, GitLab is a perfect acquisition target because it is both cheap and willing to sell itself. Shares are worth just $5.5 billion (a rounding error for SpaceX’s cash pile) and explored a sale in 2024 to Datadog Inc. (DDOG).

I also give GitLab a 1-in-3 chance of getting bought by Elon Musk’s firm.

Tier 3: The Moonshot Bets

Viasat (VSAT): Viasat is one of the best strategic fits for SpaceX, but also the most likely to get struck down by regulators.

In short, Viasat controls an estimated $15 billion worth of “L-band” spectrum – the low  frequencies that act as an “emergency lane” in satellite communications. This band is great at passing through clouds and is very dependable on moving ships, aircraft, and cars. However, there is very little L-band spectrum available, so it is usually reserved for critical situations.

SpaceX would almost certainly love to own this bandwidth. The company could offer Starlink’s higher-frequency “Ku” and “Ka” bands for speed, and switch to L-band whenever a cloud passes by. The company would also pick up Viasat’s customers and regulatory approvals. I would, however, only give SpaceX a 1-in-6 chance to make a move, given the number of governments that might oppose a deal.

6. Gogo Inc. (GOGO). Gogo is the name for in-flight Wi-Fi for private jets. The company serves roughly two-thirds of that market and has a nationwide backup network that uses ground towers for whenever satellite connection is obstructed.

An acquisition would accelerate Starlink’s move into business jets. Gogo already has sales agreements with every major business aircraft maker, and has its equipment installed on more than 7,000 aircraft. Starlink has been fighting hard for market share, so an acquisition would free up precious resources for other ventures. Gogo’s shares are also quite cheap – down 75% in the past year – and the company comes with the ground-based backup network that SpaceX might like to have.

Like Viasat, I give Gogo a 1-in-6 chance of getting acquired.

SentinelOne Inc. (S): Last week, I wrote how Alphabet Inc.’s (GOOGL) $32 billion blockbuster acquisition of digital security firm Wiz was a sign of more cybersecurity acquisitions to come. AI data centers need to protect their users, and some providers are moving this service in-house.

SpaceX might be tempted to do this as well as it builds out AI tools for business. And one of the most obvious cybersecurity firms it could buy is SentinelOne, which lands in the “Goldilocks” zone for a takeover.

It’s not too big like CrowdStrike Holdings Inc. (CRWD), which serves 60% of the Fortune 500. SpaceX is probably not interested in becoming a full-blown cybersecurity provider.

And it’s not too small like Rapid7 Inc. (RPD), which offers too narrow a product lineup to protect AI data centers on its own.

Instead, SentinelOne is just right because it offers a wide enough product range without threatening to eclipse SpaceX’s AI ambitions. Its Singularity Platform is considered a one-stop shop for threat detection and response.

Best of all, SentinelOne is a company I would be willing to recommend at current prices. Its business has a relatively wide moat, and its Singularity Platform is best-in-class. So, even if no offer ever comes, the company should keep growing on its own. Either way, shareholders win.

Getting in on the Ground Floor

It’s usually quite wonderful to own a publicly traded company that is getting bought out. Most buyers will offer a premium of about 30% to pre-deal share prices, and high-growth companies usually get better sweeteners.

Anyone who owned Slack before its 2020 acquisition by Salesforce Inc. (CRM), for instance, would have earned a 55% return from the pre-rumor price.

It’s even better to own an unlisted startup when buyers come knocking. Cursor’s 100% premium was quite low compared with other purchases like Alphabet’s acquisition of Wiz (167% premium) and Okta Inc.’s (OKTA) bid for Auth0 (239%). These smaller firms know they are trophy assets, and so will demand a price tag to suit them. Even the most ardent buy-and-hold investors have a price they should be willing to sell at.

In his latest presentation, 2026 Megadeal Event, Luke walks us through exactly how to identify and buy these deals… even if they aren’t on the market yet. If SpaceX keeps shopping at this pace, the next megadeal may already be in the works.

Check it out here.

Until next week,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post SpaceX Needs Growth… Here Are 7 Companies It Might Buy appeared first on InvestorPlace.

Jeff Bezos called it “Mechanical Turk,” after an 18th-century chess-playing machine that toured Europe astonishing kings and philosophers who assumed they were losing to a clockwork mind. The trick, as it were, was a human chess master working the machine’s arms secretly from inside the cabinet.

Amazon’s Mechanical Turk was the same kind of Trojan Horse.

Any task that a computer couldn’t handle – like labeling photos, transcribing clips, validating addresses – shot out to a vastly dispersed workforce who did the work for pennies apiece. To the user, the results seemed like the output of a machine.

Bezos had a name for that arrangement: “artificial artificial intelligence.”

It wasn’t exactly glamorous to pitch, which would be something like Mechanical Turk “pays strangers small amounts to look at pictures all day.” But that unglamorous task has been behind almost every meaningful advance in machine learning for the past twenty years. Every model that “sees” a stop sign or “understands” a sentence first needed to be shown thousands of correctly labeled examples by somebody. Someone always has to do the boring job of telling the machine what it’s looking at.

Meta Put Billions Behind Scale AI’s Data Engine

In 2016, a 19-year-old named Alexandr Wang dropped out of MIT after his freshman year. He left with one narrow observation: every company racing to build machine learning products found their bottleneck in clean, accurately labeled data to train those algorithms on. Nobody had yet built a real business around solving that specific problem at scale.

Wang and co-founder Lucy Guo built one anyway. They called it Scale AI, and its early customers were companies trying to teach self-driving cars to recognize what a camera was actually seeing. On paper, it was one of the least exciting business ideas in Silicon Valley: a company that helps other companies label their data.

Last year, Meta (META) decided that unglamorous labeling business was worth $14.3 billion, investing in Scale AI for a 49% stake and hiring Wang away to become the company’s chief AI officer. The job itself hadn’t changed much since 2005. What changed was how many companies suddenly needed it done well, at a scale no single one of them could build for itself overnight.

Tesla Turned Its Fleet Into an AI Training Data Engine

Tesla (TSLA) found a different way to solve the same problem, and it may be the more instructive version of this story.

Rather than hiring an army of human labelers, Tesla built the job directly into its product. Every Tesla on the road runs what the company calls “shadow mode”: the car’s self-driving software quietly makes its own decisions in the background, even while a human is driving, and flags every moment where it would have done something different.

Multiply that across millions of ordinary commutes, school runs, and road trips, and Tesla ends up holding a dataset of real-world driving decisions that a smaller, dedicated test fleet could never generate, no matter how much money sat behind it.

Bottom line: A competitor can write a check for engineers, but writing a check for a decade of real-world driving data is a different problem entirely.

Robotics Is Creating the Next AI Training Data Bottleneck

I’ve said before that I think the next version of this exact bottleneck is forming in robotics. A language model can train on text because the text already exists, scattered across the internet, free for the scraping. A robot learning to fold laundry or bus a table has no equivalent shortcut.

Every skill must be demonstrated physically, recorded, and labeled one motion at a time, and that process remains slow and genuinely expensive even as the tools around it improve.

Which means the same question that made Mechanical Turk’s workers, Scale AI’s labelers, and Tesla’s own customers unknowingly valuable is about to get asked again: who is quietly doing the boring job nobody else wants, at a scale nobody else can match?

History suggests the answer is worth more than it looks.

Fittingly, Amazon confirmed that Mechanical Turk – the original artificial artificial intelligence, the job that started this entire pattern back in 2005 – stopped accepting new customers as of July 30.

Two decades after Bezos built a marketplace to hide human labor inside a machine, the job it invented closed its doors on the same day I revealed the startup where I believe that overlooked layer of value is forming next.

Where the Next AI Data Moat May Be Forming

I revealed this at my free 2026 AI Megadeal Event earlier this week, but it’s not too late to watch it.

You will see who is building the company, what its technology does, why the timing matters, and which risks could derail the thesis.

I also explained how the offering works and revealed the deal recommendation – completely free.

The opportunity is expected to close within a matter of weeks. But honestly, it could reach capacity even sooner.

No responsible investor can promise you the next Google. Anyone who does should immediately lose your trust.

What I can promise is to show you the work.

Check out the replay of The 2026 AI Megadeal Event now.

The post Nobody Wanted This Job, and Now It’s the Most Valuable Skill in AI appeared first on InvestorPlace.

Wall Street loves a big number, and Microsoft Corp. (MSFT) delivered several this week.

First, on Wednesday, the company reported its fourth-quarter earnings results. Earnings reached $4.81 per share, up from $3.65 per share a year earlier. Revenue came in at $90 billion, beating expectations of $87.6 billion, while Azure cloud revenue surged 43%.

Microsoft also plans to spend $175 billion on AI infrastructure this year.

But one number stood out above the rest: Microsoft’s Remaining Performance Obligations (RPO) backlog rose 84% to $678 billion.

RPO is the official accounting term for a specific type of backlog – the contracts Microsoft has signed but hasn’t fulfilled yet.

But does a bigger backlog actually prove AI is profitable?

The market certainly thought so. Microsoft shares jumped 15% on Thursday following its blowout report. Semiconductor stocks also rebounded strongly on the numbers. The Philadelphia Semiconductor Index – which tracks 30 leading semiconductor firms – jumped about 6.7%, ending a five-day losing streak.

But there’s an important distinction being overlooked: Future revenue is not the same thing as future profits.

I think investors are getting too excited about Microsoft’s future AI revenue – especially before knowing whether it will actually turn into profitable cash.

So, in today’s Smart Money, let’s take a look at why Wall Street may be celebrating AI profits before they actually arrive.

Then, I’ll share one company that is already turning AI investments into real business results.

A Bigger AI Backlog Doesn’t Mean Bigger Profits

Microsoft’s RPO is significant, but it isn’t cash in the bank.

RPO is like a restaurant with booked with dozen’s of $40-per head banquets. That’s great because demand is strong. But food still has to be bought, staff has to be paid, and meals have to be served before those reservations turn into profits.

Revenues are fixed, but costs aren’t. 

When Microsoft signs a long-term contract with a customer to provide cloud or AI services over a period of time, the amount of revenue it will receive is largely fixed. But the cost of delivering those AI services is not.

If expenses such as AI chips, electricity, data centers, or labor continue to rise, Microsoft could end up making less profit than investors expect. In other words, a growing RPO shows that Microsoft has secured future business, but it doesn’t reveal how profitable that business will be.

A signed contract is only valuable if the customer can ultimately pay. A company like OpenAI, which accounts for about one-third of Microsoft’s RPO, might not be “good for it” down the road. 

Investors are acting as if this future revenue is already earned, but it isn’t.

And Microsoft’s financials suggest the cost of delivering AI is already increasing.

• Cloud gross margin fell from around 67% to 65%. That means Microsoft is making slightly less profit on every dollar of cloud revenue.

• Overall company gross margin also declined. So, profitability is slipping across the business, despite strong revenue growth.
• Capital spending (CapEx) keeps rising. Microsoft spent $41 billion this quarter on infrastructure and expects to spend even more next year. This suggests that the cost of building and operating Microsoft’s AI business is rising quickly.

Microsoft’s surge this week shows that the market is treating bigger RPO like bigger profits.

But that isn’t necessarily true.

The company clearly has a large backlog of AI business. And a growing backlog tells us that customers want AI. But what it doesn’t tell us is if those AI contracts will generate strong profits.

I think investors are celebrating a victory before it has been achieved… just like they’ve been doing with lots of other high-profile AI names.

The bigger takeaway here is that the winners of the next phase of the AI boom won’t just be the companies spending the most, but the ones that can prove their AI investments are generating returns.

With that in mind, here’s a better “match” instead…

Wall Street Swiped Left. AI May Swipe Right.

Match Group Inc. (MTCH) is in the business of making online love connections, but the company hasn’t been able to make a love connection with investors for several years. Most of them have been “swiping left” – i.e., saying “no thanks” – on the shares of this online dating leader.

But the company’s new management is engineering an AI-powered overhaul that could produce a new era of robust earnings growth.

On the consumer side, Match is deploying AI to reshape its most important brands, Tinder and Hinge. At Hinge, for example, a new AI-powered recommendation algorithm launched in March 2025 has increased matches and contact exchanges by 15%. This meaningful improvement translates into more real-world dates and higher rates of payer conversion.

On the Tinder app, which is facing sharp user declines, Match is introducing an even broader suite of AI tools. This AI-enabled upgrade is prioritizing deeper compatibility and better user outcomes, rather than optimizing for superficial swiping or other short-term engagement metrics.

By embedding AI at multiple touchpoints – from onboarding and match recommendations to internal product development – Match is building a unified ecosystem where data, technology, and human creativity reinforce each other.

This dual focus on consumer experience and operational efficiency is not simply an experiment; it is the strategic foundation for the company’s revitalization plan.

While Microsoft spends billions to build the infrastructure needed to power AI, Match is using the technology to make its existing apps more effective – and helping turn more users into paying customers.

Match is set to release its second-quarter 2026 earnings next week. And it currently offers a unique and compelling opportunity: It is successfully using AI to reinvent its business and drive future growth.

To learn about more companies turning AI investments into real business growth, click here.

Regards,

Eric Fry

The post Microsoft Has the AI Backlog, But This Company Has the Returns appeared first on InvestorPlace.

This morning (Friday), when the alarm buzzed, my first instinct wasn’t to get out of bed.

It was to hit snooze.

Outside, it was still dark. The bed was warm. There wasn’t a single part of me that wanted to throw off the covers and start the day.

I already had a decision to make, and I hadn’t been awake for 10 seconds. More sleep or get up and exercise.

So, I got up.

Then came the next decisions. Coffee or not? Eggs or cereal? Which shirt? Which route to take to work?

By the time I sat down at my desk, I’d already made dozens of decisions – and those were only the ones I could remember.

Credit: baona

Researchers estimate we make somewhere between 20,000 and 35,000 decisions every day.

You decided to keep reading this essay, or not. You decided to take a sip of your coffee, or not. You decided to move your foot, or scratch your nose, or shift in your chair.

Or not.

Most decisions happen so quickly and so automatically that we barely notice them. That’s because our brains are designed to conserve energy. If we stopped to carefully analyze every choice, we’d never get anything done. So instead, we rely on mental shortcuts that let us make “good enough” decisions almost instantly.

Most of the time, that’s a remarkable advantage. But it can be a dangerous mistake when investing.

The problem is that our brains are wired to react efficiently rather than to think independently.

The stock market is simply millions of people making decisions with those same kinds of shortcuts.

Investors don’t just react to earnings reports or economic data. They react to headlines. They react to what everyone else is buying. They react to the stories dominating the news.

In other words, the market often reacts first… and thinks later.

Scale those individual decisions up across millions of investors, and those mental shortcuts become market sentiment.

The Market’s Blind Spot

Investing legend Louis Navellier has spent decades reminding investors of a simple truth. To this day, he says it frequently on his podcasts and in his newsletters.

In the short run, markets are driven by emotion and investor sentiment. But over the long run, they’re driven by something much more powerful: fundamentals.

That’s why Louis has never built his investment strategy around the market’s latest sentiment-based obsession. His Stock Grader system was designed to identify fundamentally superior companies that don’t need fickle emotions to drive them higher – instead, their performance is far more durable thanks to superior fundamentals. Which brings us to artificial intelligence.

Investors see ChatGPT. They see Nvidia (NVDA). They see the companies that powered AI’s first great breakthrough.

But that’s exactly what mental shortcuts encourage us to do. We naturally focus on what’s already obvious.

Louis believes that may be causing investors to overlook something far more important: the next phase of AI, one that’s beginning to emerge while most of Wall Street is still fixated on the first.

This week, the market, and AI stocks in particular, experienced outsized volatility. Concerns that the AI trade was overextended, and uncertainty about the Federal Reserve’s interest rate policy had left people feeling edgy. Then reports surfaced that Chinese tech companies would undercut U.S. AI companies.

That sent markets reeling.

As he usually does during times of market volatility, Louis reached out with a podcast exclusive for Growth Investor subscribers. Here was his bottom line:

China is developing AI. They’re pretty good at it, but we’re better. And most of the big U.S. companies will be using the U.S. AI.

So, don’t worry about that. That’s just another thing that people throw out there to try to attack the market.

The bottom line is that order backlogs are growing. The AI boom continues. We can’t stop it.

Either you get on board, or you get left behind. That’s where we are.

Choosing Fundamentals Over Fear

Louis’ system of selecting only fundamentally superior stocks showed up in this week’s earnings.

Bloom Energy Corporation (BE) soared on Tuesday evening and Wednesday after the company achieved record revenue, crushed analysts’ earnings expectations and increased its full-year outlook.

If you’re not familiar, Bloom Energy has been a big beneficiary of the AI boom. The company designs and manufactures solid oxide fuel cells and electrolyzers that provide clean, reliable, on-site electricity generation for data centers without combustion.

The two weeks prior to the report, Bloom had sunk almost 30% as it was caught up in the same AI selloff as the rest of the market. But the earnings story continues to show why it is a quality stock in Louis’ system.

Second-quarter revenue soared 165.5% year-over-year to $1.065 billion, marking the first time that the company achieved revenue more than $1 billion. Earnings surged 680% year-over-year to $0.78 per share. Analysts expected earnings of $0.41 per share on $827.02 million, so Bloom Energy posted a 90.2% earnings surprise and a 28.8% revenue surprise.

Company management boasted, “Bloom is now the standard in AI onsite power.” They noted that all the major hyperscalers in the U.S., as well as neoclouds, AI labs and colocation data centers, utilize Bloom Energy’s fuel cell solutions.

Looking forward, Bloom Energy now expects full-year 2026 revenue between $3.9 billion and $4.2 billion and earnings per share between $2.55 and $2.85. That represents 93% to 108% annual revenue growth and 235.5% to 275% annual earnings growth.

One of Louis’ favorite phrases is that quality stocks “bounce like fresh tennis balls.” You can see the solid earnings reflected in the last few days of trading after the earnings report.

While the AI trade is still under pressure, superior earnings will always fuel a bounce.

Bloom Energy is a reminder that reacting to headlines and understanding what’s happening are often two very different things.

Remember those mental shortcuts we all rely on?

Right now, they may be encouraging millions of investors to ask the wrong question.

They’re asking whether today’s AI winners can keep winning.

Louis is asking a different question:

Which companies stand to benefit from the next evolution of artificial intelligence?

That question and the answers his Stock Grader has uncovered are the focus of his new presentation.

You can learn all about Louis’ list of stocks for the next phase of the AI revolution by clicking here.

Our brains are wired to react to what’s obvious. Successful investing often comes from seeing what isn’t.

If you’d like to see where Louis believes AI’s story goes from here – and the stocks he believes could benefit most – I encourage you to join him for this special presentation.

Enjoy your weekend,

Luis Hernandez

Editor in Chief, InvestorPlace

The post Investors Are Looking at AI the Wrong Way appeared first on InvestorPlace.