That is why my InvestorPlace colleague Louis Navellier is joining us today to show you why Huang’s latest moves could reveal where the next opportunities are hiding.

He’ll also explain what Nvidia’s strategy can teach us about building a portfolio where every position has a purpose. Because the challenge today isn’t simply finding another AI stock; it’s knowing which opportunities deserve your money, how much to put into each one, and how they fit together.

That’s exactly why Louis Navellier, Luke Lango, and I brought together our best-in-class ideas to create the AI Revolution Portfolio: Just 19 positions we believe represent some of the most powerful AI and technology opportunities available today.

You can learn more about our AI strategy here. Now, here’s Louis…

In chess, the Queen’s Gambit begins with what looks like a sacrifice.

Despite the name, you don’t give up your queen. You offer a pawn, accepting a little risk early in exchange for something potentially far more valuable: control of the center of the board.

Here’s what the setup looks like…

(Credit: chess.com)

It’s a strategy that has been used at the highest levels of chess for generations. Garry Kasparov, one of the greatest players in the history of chess, repeatedly battled through Queen’s Gambit positions during his legendary World Championship matches with Anatoly Karpov.

Lately, I’ve been wondering whether Jensen Huang is playing his own version of the Queen’s Gambit at NVIDIA Corporation (NVDA).

For years, Huang has been willing to put billions of dollars of NVIDIA’s capital at risk across the AI ecosystem. NVIDIA has put roughly $30 billion into OpenAI. It has invested billions in CoreWeave, Inc. (CRWV), Nebius Group N.V. (NBIS), Marvell Technology, Inc. (MRVL), Synopsys, Inc. (SNPS), Coherent Corp. (COHR), Lumentum Holdings Inc. (LITE), IREN Limited (IREN) and Corning, Inc. (GLW) – many of which turn around and spend heavily on NVIDIA’s GPUs and infrastructure.

It also owns major stakes in Intel Corp. (INTC) and Space Exploration Technologies Corp. (SPCX).

Critics have a name for that: “circular financing.”

Their argument is straightforward. NVIDIA gives money to AI companies. Those companies use some of that money to buy NVIDIA products. NVIDIA books the revenue, makes more money and invests even more back into the ecosystem.

Looked at one way, that can seem dangerously self-reinforcing.

However, I think Huang may have been sacrificing a few pawns to gain control of the center of the AI board.

And now he’s made two moves that could change the game entirely.

So, today, let’s look at how Huang’s Queen’s Gambit has worked so far… the two new moves that could tighten NVIDIA’s grip on the AI economy… and whether the king of AI is getting closer to checkmate.

The Gambit

First, it helps to understand just how aggressive NVIDIA has become as an investor.

Between 2021 and 2025, NVIDIA participated in 283 funding rounds involving 241 different companies. Nearly 85% of them were AI startups.

Its investments now stretch across nearly every layer of the AI ecosystem.

The strategy is fairly easy to understand.

AI companies need extraordinary amounts of computing power. But GPUs, data centers, networking equipment and power infrastructure are extremely expensive. Younger companies in particular may not have enough capital to build everything they need.

So, NVIDIA helps provide it.

That capital allows these companies to expand their AI infrastructure. And much of that infrastructure, naturally, runs on NVIDIA technology.

Critics argue that this creates a circular system.

NVIDIA invests money in a company. The company buys NVIDIA GPUs. NVIDIA generates more revenue. And NVIDIA can then invest even more money across the AI ecosystem.

I understand why that makes some investors nervous.

If AI spending eventually slows sharply, NVIDIA could feel the impact twice – first through weaker demand for its core products and again through falling values across the companies and projects it has financed.

But there is another side to this strategy.

Every dollar NVIDIA invests can help remove one of the biggest bottlenecks facing the AI boom: access to compute.

And every new data center built around NVIDIA hardware makes its ecosystem a little harder to displace.

That’s the gambit.

Huang is accepting additional financial exposure in exchange for greater control of the center of the AI economy.

And now he appears to be taking that strategy to another level.

Is “Checkmate” on the Horizon?

The first major move came on August 10.

NVIDIA announced agreements with Apollo Global Management, Inc. (APO), BlackRock, Inc. (BLK), Blackstone Inc. (BX), Brookfield Corporation (BN), Goldman Sachs Group, Inc. (GS) and KKR & Co., Inc. (KKR) to establish independent financing platforms designed to mobilize more than $500 billion of third-party capital for AI infrastructure.

Think about what Huang is doing here.

Instead of NVIDIA having to provide all the money required to keep the AI buildout moving, some of the largest pools of capital on Wall Street can help finance it.

The platforms are designed to fund GPUs, data centers, networking equipment, power infrastructure and other components needed by hyperscalers, AI labs and enterprises. NVIDIA itself describes the goal as turning AI compute into an “investable asset class” for global capital.

And NVIDIA still gets to sell the hardware.

That alone strikes me as a very clever answer to the circular-financing criticism.

If Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are willing to put outside capital behind these projects, it becomes harder to argue that NVIDIA is simply manufacturing demand by financing its own customers.

But then Huang made another move.

On Monday, NVIDIA announced a major new arrangement involving OpenAI and SB Energy (owned by Softbank) at the PORTS-Pike Technology Campus in Ohio.

OpenAI has agreed to use roughly 8 gigawatts of computing capacity at the campus under a 20-year lease. And every bit of that AI compute infrastructure will run exclusively on NVIDIA technology.

NVIDIA, meanwhile, is investing $1.5 billion in SB Energy and providing credit support for the land, power and shell infrastructure needed for the initial 4.25 gigawatts of capacity. NVIDIA also has an option tied to the remaining 3.75 gigawatts.

This deal certainly won’t silence every circular-financing critic. NVIDIA is still putting capital at risk to help secure infrastructure for one of its biggest customers.

But let’s look at the whole board Huang is creating.

OpenAI gets the computing capacity it needs. SB Energy builds and operates the data center. Wall Street and infrastructure investors increasingly provide the capital.

And NVIDIA supplies the GPUs, CPUs, networking and full-stack systems at the center of it all.

That’s why I’m reluctant to dismiss these deals as simple financial engineering.

Huang may be building something much larger.

For years, NVIDIA has been the arms merchant of the AI Revolution.

Now it is helping build the financial system that allows its customers to keep buying the arms.

I wouldn’t call checkmate just yet. There are still plenty of pieces on the board, including Advanced Micro Devices, Inc. (AMD), Alphabet, Inc.’s (GOOG) custom chips and a growing number of companies developing their own AI silicon.

But Huang is making it increasingly difficult to compete with NVIDIA on chips alone.

You may now have to compete with its software. Its networking. Its enormous installed base. Its relationships throughout the AI ecosystem.

And increasingly, the financing infrastructure surrounding all of it.

That is a formidable position, folks.

The Next Move for AI Investors

I’ve been bullish on NVIDIA for years, and that hasn’t changed.

The stock has made my subscribers a tremendous amount of money, and I continue to believe NVIDIA is one of the premier companies of the AI Revolution.

But there’s an important lesson in Huang’s strategy for individual investors, too.

Chess isn’t won simply by having the most powerful piece on the board. It’s won by understanding how all the pieces work together.

And that’s becoming increasingly important for investors as well.

That’s why my special event this week with my InvestorPlace colleagues Luke Lango and Eric Fry was so important.

See, Luke, Eric and I have identified a tremendous number of opportunities throughout this AI Revolution. Over the past year alone, we’ve collectively issued more than 200 recommendations.

But here’s what’s different now.

We’ve taken the very best of those ideas — the highest-conviction, most powerful opportunities across all three of our research teams — and built something new: a concentrated portfolio of just 19 positions.

Just 19 of what we believe are the absolute best AI and technology opportunities available today.

Think of it as applying the principles of chess to investing – where every position has a purpose, and every holding is chosen because it strengthens the whole board.

See where I’m going with this?

The challenge now isn’t simply finding another AI stock we like. It’s figuring out which opportunities deserve your money, how much belongs in each one and how all those investments should fit together.

That’s a major reason why, after 47 years, I’m making the biggest change to my role at InvestorPlace in decades.

During our special event, I sat down with Luke and Eric to explain exactly what’s changing – and how we plan to approach the AI opportunity differently from here.

I’m not retiring. But I’ve come to believe that finding great stocks is only one part of the job.

Click here to watch the replay.

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), Advanced Micro Devices, Inc. (AMD), Coherent Corp. (COHR) and NVIDIA Corporation (NVDA)

The post Here’s What NVIDIA’s $500 Billion “Checkmate” Means for Investors appeared first on InvestorPlace.

At the start of 2021, Nvidia Corp. (NVDA) was a $330 billion company. It had a significant data-center business, but still mostly built chips for gaming computers and consoles. 

As you well know, Nvidia would transform into an AI behemoth. ChatGPT debuted in late 2022, a massive AI data-center buildout began the following year, and Nvidia is now the most valuable company on Earth. Investors during that stretch enjoyed a roughly 940% return. 

One by one, other AI-related companies have also seen their “Nvidia moment” arrive: 

• First, it was semiconductor companies like Broadcom Inc. (AVGO) and Advanced Micro Devices Inc. (AMD). 
• Next came the data-center infrastructure firms, such as Super Micro Computer Inc. (SMCI) and Arista Networks Inc. (ANET). 
• Then memory-chip makers went vertical. Micron Technology Inc. (MU) and SanDisk Corp. (SNDK) became household names.  

And every time, many investors watched from the sidelines as a new group of stocks zoomed ahead. Even those lucky enough to get in would often wonder, “Why didn’t I buy more?” 

Fortunately, there are still companies that are only at the beginning of the AI Revolution. 

In a new special presentation, our three senior analysts – Louis Navellier, Eric Fry, and Luke Lango – join forces to talk about their AI Revolution Portfolio: a carefully selected group of 19 stocks that still have room to grow thanks to this new technology. They believe we’re reaching a point where AI is going super exponential and turning 10X returns from a slow-motion event into something that can happen in months… or even days. 

You can watch their free presentation here. 

To give a sense of the opportunity, I’d like to highlight several other picks that are still being overlooked by Wall Street. And to get the full details on their AI Revolution Portfolio – and a little bit more on their 19 official picks – click here to watch the special event. 

The Eyes of the AI Revolution 

Earlier last week, Chinese firm Unitree Robotics surged 629% after listing in on the Shanghai Stock Exchange. 

You probably recognize the company from viral videos of its backflipping, dancing robots – moves I can only dream of doing.  

Unitree’s $13,500 G1 humanoid robot costs a fraction of what competitors charge, and the company has already set up an “app store” for owners to download more skills. It’s easy to see a future where Unitree robots gain new abilities like “nanny mode” or “master electrician” at the click of a button. 

While I do believe the firm will succeed in the long run, I do not recommend trying to buy this one stock. Shares were at least 5,500 times oversubscribed, and its abnormal first-day pop reflects China’s peculiar trading rules. In fact, Unitree soon fell around 20% after its IPO, leaving new investors with immediate losses. 

Unitree investors are buying hype right now, and I never like buying hype by itself. That’s why I would recommend a “picks-and-shovels” play instead. 

It’s a company that supplies vision systems for Unitree’s robots… 

It ships 60% of the “eyes” of all robotaxis… 

And best of all, shares are barely higher than they were at the start of 2025. 

This company is Hesai Group (HSAI) 

Hesai has spent the past several years consolidating the market for lidar sensors – the devices that use lasers to map the world around vehicles and robots.. It has driven at least a half-dozen competitors out of the business, and now supplies 8 out of the top 10 robotaxi companies globally. Hesai also counts major robotics manufacturers as customers, including Unitree. 

The company did this with a cutthroat pricing strategy, which has kept share prices low. Operating margins were just 5.6% in 2025, and investors rightly stayed away. HSAI trades a hair below its 2023 listing price, even as AI-driven demand from robotaxis and humanoid robots have pushed ahead. 

But Hesai is finally winning the lidar war. Analysts expect operating margins to hit 13% this year, 15% in 2027, and then 18% in 2028. That means Hesai is already on its way to transforming from a low-returning company like General Motors Co. (GM) to a high-returning one like Sensata Technologies Holding PLC (ST) – a specialist auto-parts manufacturer. 

Now, this flip to higher profits is happening right as robotaxi growth is reaching an inflection point. Self-driving car companies are rapidly expanding in cities like Los Angeles, Beijing, and Dubai, and many are projecting 100%-plus annual fleet growth thanks to sudden improvements in AI-powered self-driving technologies. 

Meanwhile, more and more people – including myself – are becoming OK with getting chauffeured around by these driverless cars. 

That matters because robotaxis require far more lidar units than ordinary cars. Some carry as many as eight Hesai sensors to eliminate blind spots. Many higher-end passenger cars are also beginning to use multiple lidar rigs to enable “Level 3” self-driving – the type that allows drivers to take their eyes off the road. Humanoid robots will only add to this eventual demand. 

Of course, Hesai is not a risk-free investment. The company exports products to America, which has put up numerous trade barriers in recent quarters. The firm also has a customer concentration issue due to the sheer size of some robotaxi customers; the top 5 customers made up more than half of 2025 revenues. And, of course, a new price war could break out if a well-funded firm decides to start selling lidar components as well. 

Nevertheless, the risk-reward looks considerably better than chasing a robotics IPO that opened 629% higher on its first trading day. Hesai does not need Unitree to become the world’s dominant robot maker. Nor does it need Baidu Inc. (BIDU), PonyAI Inc. (PONY), or WeRide Inc. (WRD) to win the robotaxi race. 

It simply needs autonomous machines to keep proliferating. And that is something the AI Revolution almost guarantees will happen. 

And the Brains 

The bull story for this next stock is simple: 

China is becoming a powerhouse in AI, and Beijing badly wants its homegrown companies to win. 

To capitalize on this trend, I would recommend shares of the country’s most established AI firm: Alibaba Group Holding Ltd. (BABA). 

The e-commerce giant has pursued Amazon.com Inc. (AMZN)-style vertical integration. It designs its own chips, runs its own data centers… and even builds its own AI models 

Chips. The country lacks the specialized machinery used to make high-performance GPUs, and so Alibaba’s designers have developed clever workarounds. For instance, their “Panjiu” servers use 128 AI accelerators rather than the 72 that Nvidia uses. This brute force method helps offset weaker chips. 

Models. Its Qwen family of AI models captured 30% of self-hosted AI usage at the end of 2025 (that’s when you download an AI model to run for yourself), and it has since created some of the best AI models in the world. Its latest model, Qwen3.8 Max, is almost as good as Claude Fable 5, Anthropic’s most advanced model. It even beats Fable in certain tests like operating normal desktop computers. 

Datacenters. Superior chips and models have allowed Alibaba to provide cloud computing that is both effective and cheap. Its flagship Qwen3.8 Max model costs barely a third of Claude’s Fable 5 to run, and these leading models have helped Alibaba gain a 40% market share of China’s AI cloud computing market. That puts it ahead of the three next companies combined – ByteDance, Huawei, and Tencent. 

Meanwhile, Alibaba’s e-commerce side is a cash cow. Earlier last week, the company reported that its global e-commerce sales increased 4%, and that adjusted earnings before interest, taxes, and amortization (EBITA) from the segment hit $5.9 billion. That figure easily offsets the $2 billion of losses its Cloud Intelligence segment currently generates from its heavy investments.  

Best of all, Alibaba has not yet hit its “Nvidia moment.” The stock has fallen 19% since 2021 when Nvidia was beginning its epic run and trades at a discount to its Chinese peers. 

I must note that Alibaba faces regulatory issues. The Chinese government “disappeared” the company’s co-founder in 2020 after he gave a speech that criticized the country’s financial regulators; it could do something similar again if the company steps out of line. China is also planning its own state-led data center buildout, which could cap profits in that sector. 

Nevertheless, these risks are already priced into Alibaba’s shares. The company trades at just 19X forward earnings and is worth less than Nvidia was in 2021. In my view, this sets Alibaba up for its own “Nvidia moment.” 

Riding The AI Revolution 

One of the most common questions I get asked is, “Are we in another dot-com bubble?” 

That’s smart to ask. Things turned out badly the last time investors went head over heels for a new technology. 

But here’s what’s different from the 1990s. 

You see, during the dot-com boom, everyone knew telecom companies were building too much capacity. By 1999, roughly half of America’s installed fiber network sat “dark,” and more than 90% of some newly constructed long-haul networks were unused. 

We saw the same pattern during the housing boom of the 2000s. Buildings went up in the middle of deserts and swamps… and they had no residents. 

The AI Revolution different. Today, companies are struggling to build enough cloud computing capacity because everything is bottlenecked. Roughly 40% of AI data-center construction projects are now delayed until next year, and certain components like flash memory and hard drives are sold out until 2028. 

That’s why Louis, Eric, and Luke believe there’s still plenty of room for the rally to run. So, be sure to watch their AI Revolution presentation before that next company you’ve had your eye on reaches its “Nvidia moment” before you’ve had a chance to get in. 

I will be out of town the next two weeks for travel, and so I’ll see you back here after Labor Day. 

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 2 Stocks to Buy for the AI Revolution  appeared first on InvestorPlace.

For months, crypto investors have been stuck in the interhalving dead zone. And the right move was to stay on the sidelines until the market handed us real evidence that the next boom cycle is starting to turn.

This week, for the first time since this dead zone began, we got some of that evidence.

On Wednesday, President Trump hosted crypto executives at the White House and said his administration is “considering” sizable purchases of Bitcoin (BTC/USD) and other digital assets, while again calling on Congress to pass “a fair version” of the CLARITY Act.

Bitcoin ripped through $69,000 that day.

But the more precise driver, per the same day’s reporting, was Treasury Secretary Bessent doubling the size of long-term bond buybacks, from $2 billion to at least $4 billion per operation.

That move is credited with triggering roughly $3 billion in short-position liquidations, which did as much or more to fuel the move as the crypto headlines did. The summit gave the rally a story while the short squeeze gave it its size.

The rally continued Thursday, with Bitcoin pushing toward $75,000. The same day, the CFTC’s newly formed Innovation Advisory Committee held its first meeting — 35 members, heavily weighted toward industry, with the CEOs of Coinbase (COIN), Robinhood (HOOD), Polymarket, and Kalshi in the room.

Trump also said CFTC Chair Selig is “working very hard” to bring the offshore derivatives platform Hyperliquid onshore under a compliant framework, sending its token up double digits on the remark.

The 200-day Reclaim Is the Signal That Matters

On Wednesday, Bitcoin closed back above its 200-day moving average for the first time since the death cross that formed on Nov. 16, 2025:

We went back through Bitcoin’s entire trading history and found exactly three prior instances of this specific setup: six-plus months spent below a still-declining 200-day average, followed by a reclaim.

All three — 2015, 2019, and 2023 — went on to mark major, multi-year cycle lows. Not short-lived bounces. Genuine trend reversals.

The honest caveats matter as much as the headline: this is a sample of three. Two of the three whipsawed back below the average before the real move started — 2015 gave back another 24% first.

And this specific breakout’s proximate cause, a short squeeze, is exactly the kind of fuel that powered the near-term fakeouts in the two cycles that chopped before continuing.

It’s a small, noisy sample. Still, historically, it’s clearly bullish.

The Halving-cycle Chart

Here’s what I said back in February:

It can't be this simple, can't it?

Bitcoin is just tracking the same price pattern it followed after the 2020 halving… and after the 2016 halving…

The arguments were that because of Trump, ETFs, institutional money, etc that the 2024 halving cycle would play out… pic.twitter.com/6MTcYhW5hi

That Bitcoin halving-cycle chart overlays the last three Bitcoin halving cycles, each normalized to its own starting point and plotted on a log scale.

The white line is our current cycle. The blue line is the 2019–2023 cycle. The orange line is the 2015–2019 cycle. It marks the April 19, 2024 halving, a projected cycle top around October 6, 2025, and a projected cycle bottom around Oct. 18, 2026.

Two things jump out. First, this cycle has tracked well below the trajectories of the prior two on a normalized basis — consistent with a maturing, multi-trillion-dollar asset that no longer puts up the same percentage moves it did as a small-cap curiosity.

Second, in both prior cycles, the bottom formed roughly a year after the top, followed by a strong recovery the following year.

Map that pattern onto today, and you land on a projected bottom window around mid-to-late October 2026, with a recovery into 2027.

I want to be precise about what this chart is and isn’t. It’s a pattern drawn from a small handful of completed cycles — a rough signpost, not a guarantee. But paired with this week’s 200-day reclaim, it’s a second, independent line of evidence pointing in the same direction: the worst of the dead zone may be closer to its end than its middle.

What We’re Not Calling a Signal Yet

Trump’s purchase comments are not new information. “Considering sizable purchases” is the same mechanism-free language the administration has used since the March 2025 Strategic Bitcoin Reserve executive order — no budget authorization, no dollar figure, no timeline, no path around the budget-neutral constraint that’s boxed in every version of this idea so far.

We flagged nearly identical language after an earlier summit weeks ago and called the pattern “buy the rumor, sell the fact.” Nothing about the substance has changed since — only the fact that price also moved this time, which isn’t a reason to upgrade rhetoric to a confirmed signal.

The CLARITY Act is also unchanged: the Senate’s cloture vote is still set for Sept. 15, still needs 60 votes, and is still reported as roughly six Democratic votes short.

So we’re counting one confirmed signal this week: a real technical reclaim. But there are two tracks left to climb before we’d call this confirmed rather than encouraging:

Technical: a successful retest and hold of the 200-day average, currently around $69,000 and still declining — if price comes back into that zone and holds instead of failing back below it, that’s confirmation the reclaim was structural, not squeeze-driven. Above that, a reclaim of $85,000, roughly the November–December 2025 support cluster ($84,684–$86,537) that broke down in January. And above that, $82,200 — the May 2026 high, which sits almost exactly at the 50-week moving average (roughly $81,700–$82,000). That’s the cleaner, historically stronger version of this same signal, and the level we’ve flagged as the all-clear for months.

Fundamental: CLARITY Act passage. And an actual confirmed government purchase mechanism — a budget line, a dollar figure, a timeline — not a remark at a podium.

We’ve talked before about opportunistic buying in the $55,000–$58,000 range as valuation got attractive. That was always a side observation, not the core thesis.

The core thesis has always been: stay on the sidelines until the market gives us real evidence the dead zone is ending. This week, for the first time, it did.

That said, we’re not popping champagne.

There’s a long ladder of confirmation still ahead, and history says this exact setup has chopped before it worked two times out of three. But for the first time in months, this isn’t just a message to wait.

One More Thing Before You Go

Bitcoin’s dead zone thawing is one of the biggest stories I’m tracking right now. But it isn’t the only civilization-scale wealth shift I’ve got my eye on.

There’s another one brewing… and it doesn’t involve a single token or a single halving cycle.

It involves Elon Musk.

I believe Musk is laying the groundwork for what could become the biggest corporate merger in history: a combination of Tesla (TSLA) and SpaceX (SPCX) into a single entity I’m calling “XPANSE.”

Musk’s own biographer, top Wall Street analysts, and venture capital veterans have all suggested some version of this could be coming — and I believe it could dwarf what PayPal, Tesla, and SpaceX have already done for early investors.

Just like I try to do with crypto cycles, I’ve identified three specific, under-the-radar stocks I believe are positioned to benefit if this thesis plays out, well before Wall Street catches on.

I’ve put together a full briefing on it — including the name and ticker of a free pick — and I’d like to send it your way, with a risk-free trial to my daily research service, Innovation Investor.

Click here to see the full XPANSE briefing before the market catches on.

Whether it’s Bitcoin’s halving cycle or Elon’s next potential masterstroke, the game is the same: try to get positioned before the crowd figures out what’s happening. That’s what I’m here for.

Stay patient. Stay disciplined. Better days are ahead.

The post The First Crack in the Ice: Why Crypto Winter May Finally Be Thawing appeared first on InvestorPlace.

Does the barcode below ring a bell? (Or, should I say, register?)

Wherever you’ve shopped, you come across them. Billions of shoppers around the world encounter them every day. 

It’s a technology many of us overlook, but it revolutionized the checkout process. After barcode technology was adopted, it basically halved transaction times.

In 1988, Target Corp. (TGT) was among the first mass merchandisers to implement Universal Product Code (UPC) scanning, using barcodes to read prices and monitor inventory in real time.

The Minneapolis-based retailer rapidly expanded across the country in the years that followed. Of course, the barcode didn’t single-handedly drive Target’s growth, but it gave the big-box chain something invaluable: a faster, more efficient way to run its business. And the company’s sales continued climbing as the technology became part of its operations.

Now, nearly four decades later, Target is embracing another revolutionary strategy that could prove just as transformative: artificial intelligence leadership.

Last week, Target appointed Chandhu Nair as its first-ever chief AI officer (CAIO), with his tenure beginning Monday. His job will be to manage the organization’s overall AI strategy and align it directly with goals to enhance revenue, reduce costs, and promote growth.

By naming a CAIO, Target is following in the steps of industry peers like Ralph Lauren Corp. (RL) and Dollar General Corp. (DG). Businesses outside retail, such as Eli Lilly and Co. (LLY), Pfizer Inc. (PFE), and Accenture Plc (CAN), also have established CAIO roles.

In fact, an IBM study reported that 76% of surveyed organizations now have a CAIO, up from 26% last year.

That’s a remarkable shift in just one year, and it raises a bigger question: Why are companies suddenly putting AI at the C-suite level?

So, in today’s Smart Money, I’ll explore what Target plans to do with its CAIO role, what this decision signifies for the company, and how it impacts the broader AI landscape.

Then, I’ll highlight the proper ways to invest in this shift… before it really starts to “register.”

Let’s jump in…

Target’s Next Big Adoption

When Nair joined the Target team earlier this month, he explained his vision clearly: “What excites me most is the opportunity to make AI real for the people who experience Target every day.”

He elaborated on how he sees AI impacting the traditional shopping scene:

The most meaningful AI stories won’t be about what happens in a lab. They’ll be about what happens on the front line – how we make shopping easier for a guest, give a team member a better tool, make a business decision with more confidence, or bring a new idea to market faster.

Target also promoted Purvi Shah to Senior Vice President, who will work closely with Nair. Shah previously served as vice president of user experience design. Together, the two executives will help put people at the center of Target’s AI strategy – making shopping easier for customers while giving employees better tools to do their jobs.

But Target isn’t just using the technology to enhance the traditional shopping experience.  CEO Michael Fiddelke said the company is preparing for a future where AI agents may frequently shop for humans. Target is already planning how its online platform will serve both human and AI agent shoppers.

And one thing that’s likely to play a role in this evolution? Barcodes.

While AI agents may eventually handle the shopping, barcodes can help make sure the physical products they order are identified, tracked, and delivered correctly. In that sense, the humble barcode could become an important link between AI-powered shopping and the physical world.

There is an important lesson here:

Target was an early adopter of barcode technology, but it didn’t invent it. It simply recognized how the technology could make its business better and put it to work.

Now, Target is taking a similar approach with AI. It didn’t invent the technology, but it is integrating it into its operations – at every level. And if AI helps Target improve by predicting demand, managing inventory, reducing markdowns, increasing margins, and boosting sales, then Target itself becomes a beneficiary of AI advancement.

This suggests that the greatest AI opportunity might not lie with companies developing AI itself, but with those figuring out how to apply it effectively. AI Builder companies like Nvidia Corp. (NVDA), Microsoft Corp. (MSFT), or OpenAI will not be the only ones reaping the economic benefits of AI.

In fact, now we know the list of AI winners is only growing.

But while Target may be a beneficiary of AI, that doesn’t make it a good investment. That distinction is becoming increasingly important.

That isn’t to say Target is a bad company, but it may not be the best way to capture the AI opportunity. Although its AI initiatives could improve efficiency and customer experience, the technology is not yet the core driver of its sales or earnings. So, I’m not recommending it as an AI play today.

But as AI leadership continues to spread into traditional industries, choosing the right stocks is becoming harder, not easier.

What to Buy, What to Dump, and How to Allocate

Target embraced the barcode years ago and is embracing AI today – evidence that the companies that put new technology to work are the ones that come out ahead. But not every adopter is worth owning.

That’s why Luke Lango, Louis Navellier, and I have sifted through our research and rebuilt our AI Revolution Portfolio into a focused list of roughly 20 companies – and we just released our presentation where we discuss it all. Simply click here to watch it.

But what you own is only part of the equation. How much you own matters, too.

Each position in our AI Revolution Portfolio service comes with an allocation percentage. So, instead of simply recommending a certain AI stock, we’ll also show you how much weight each position should carry in your portfolio.

There’s a lot that goes into building a robust investment portfolio in today’s AI age. We want to make it easier for you. And our approach has already produced considerable results, including a 645% return in one year from Lumentum Holdings Inc. (LITE).

Like Target, Lumentum is also a beneficiary of the AI Revolution. But unlike the retailer, AI demand is becoming a direct driver of its business. Lumentum supplies optical components that help make AI infrastructure possible, and the company says that optical links are increasingly critical to AI data centers and that AI demand is driving its revenue guidance.

That’s the kind of distinction we’re looking for as we navigate the AI Revolution.

Learn more about our approach here.

Regards,

Eric Fry

The post Target Just Named Its First AI Chief — Here’s Where the Money Goes appeared first on InvestorPlace.

Don’t make this mistake when investing in the AI Revolution

Can you guess which technology this quote from The Washington Post refers to?

“The discovery and perfection of XXX is so important, so revolutionizing and so far-reaching in its effects that we need the perspective of time fully to realize the scientific situation.”

That is a quote from the January 1, 1880, issue referring to the electric light bulb.

One can only imagine how strange it all seemed. People had experienced light from candles, fires, and kerosene lamps. Some even had seen arc lights. But no one had ever experienced anything quite like what Thomas Edison was promising – light from a tiny bulb with no smoke, flame, wick, or gas.

Below is an image of Edison’s light bulb from 1879.

Credit: ZU_09

People could look at a light bulb for the first time and easily visualize it in their homes. But it’s what they couldn’t imagine that would go on to make the most difference in their lives.

The Beginning Happening Now

In a world of new discoveries, people often misjudge the significance. They underestimate what a breakthrough technology will eventually become.

As marvelous as the light bulb was, it wasn’t the end of Edison’s revolution.

It was the beginning.

Once electricity began flowing into American homes and factories, it changed everything. Soon, innovations that would have seemed unimaginable just months/years before were sprouting up everywhere.

Electric motors transformed factories. Electric refrigerators replaced iceboxes. Washing machines made household life easier. Eventually, radios and televisions transformed entertainment and communication.

Air conditioning helped reshape where Americans lived and worked. Computers and the Internet changed everything about … well, everything.

Eventually, that same electrical infrastructure would power data centers and nearly every piece of technology we depend on today.

Of course, none of that was obvious to the people witnessing Edison’s light bulb in 1879.

They could see a light bulb.

They couldn’t see what electricity and a nationwide infrastructure would make possible.

Looking Beyond the Light Bulb

Right now, when people think of AI, they think about ChatGPT, Google’s Gemini or Anthropic’s Claude.

What if those tools are AI’s light bulb? These applications are just a glimpse of a technology that will eventually become embedded in every part of our lives.

AI’s future is going to be built on AI agents at homes and offices, robotics, autonomous vehicles, personalized healthcare, disease prediction, and workforce automation at a wide scale.

Building that future will require an enormous amount of infrastructure.

So, who is selling the technology to help build out this AI future?

That’s the question investing legend Louis Navellier has been asking. As hyperscalers race to build these data centers, which partners can truly deliver at the required scale?

That line of thinking put Seagate Technology Holdings (STX) on Louis’ radar.

One of the vital components of the AI revolution and the data center boom is data storage, and Seagate is a leader. This is from Louis’ original analysis of the stock in Growth Investor.

The biggest hyperscale and cloud data centers around the world store about 90% of their AI data on hard drives. Simply put, hard drives are six times more efficient than solid-state drives (SSDs) and use four times less operating power per terabyte than SSDs. Hard drives are also nine times more efficient than NAND.

As a result, hard drives have become the backbone of AI data storage – and there is one company that develops AI-capable hard drives better than any other company: Seagate Technology Holdings plc (STX).

The stock has risen more than 250% since Louis’ recommendation and is still trading below his buy limit price.

Those are the kinds of opportunities that emerge when you stop thinking about what AI is doing today and focus more on what is coming.

Louis believes the opportunity is about to get a lot bigger. He calls it the AI Reset.

The light bulb impressed people in 1879, but it only gave them a glimpse of what electricity wired across the country could accomplish. Just like then, any AI applications that impress you today only represent a small part of what is going to come.

That next phase will require a huge amount of energy, computing power, data storage, networking and other specialized infrastructure. And that will create a new group of stock market winners.          

Louis has been digging through the market looking for the companies he believes are best positioned for this next phase of the AI buildout.

He’s laid out his complete thesis in a special presentation, including what he believes is about to change, why it could happen much sooner than most investors realize, and the companies he believes could benefit most.

You can watch Louis’ presentation right here.

The first people to see Edison’s light bulb weren’t wrong to be amazed. They simply couldn’t see far enough ahead.

Nearly 150 years later, investors may be making the same mistake with AI. The breakthroughs we’ve witnessed so far have already been extraordinary.

But if Louis is right about what’s coming next, the most important part of the AI revolution may be the part we haven’t seen yet.

Enjoy your weekend,

Luis Hernandez

Editor in Chief, InvestorPlace

The post That AI Breakthrough That Is Still Coming appeared first on InvestorPlace.

Duncan was still one of the greatest basketball players in the world. But he was getting older.

The two had already won four championships together. And Popovich knew that squeezing every possible minute out of his star during the regular season wasn’t necessarily the best way to win another one.

So, the longtime San Antonio Spurs coach began to carefully manage Duncan’s workload.

Duncan was still tremendously valuable. But by his mid-30s, coach “Pop” simply couldn’t risk having Duncan carry too much of the team’s load. So, he generally kept his regular-season playing time to about 30-32 minutes per game.

Sometimes, he would have him completely sit out the second game of a back-to-back night.

On the official injury/inactive report, Pop would famously list Duncan’s reason for missing a game as simply: “old.”

See, coach Pop’s job wasn’t to play Tim Duncan as much as possible. His job was to put the Spurs in the best possible position to win.

The same principle applies to your portfolio, folks.

Finding the right stock is important. But you also have to decide how much money that stock deserves, how it fits with everything else you own and when its role should change.

So, in today’s Market 360, I want to discuss one of the most overlooked decisions in investing: position sizing and allocation. And I’ll show you how Luke Lango, Eric Fry and I are putting that idea into practice with the newly rebuilt AI Revolution Portfolio.

A Great Stock Isn’t a Portfolio

Investors naturally spend most of their time asking one question: “What should I buy?”

I understand why. That’s the fun part.

But there is another question that can be just as important: “How much should I buy?”

Suppose you identify a fantastic stock that eventually triples. If you put only 1% of your portfolio into it, you made a terrific call. But that winner may not have a dramatic impact on your overall wealth.

Now consider the opposite situation. You get excited about a speculative company and put 25% of your money into it. Then the stock falls 50%.

That one mistake just cost you dearly. It might mean the difference between retiring early or waiting a few more years.

A vacation home – or downsizing in retirement.

That is why position sizing matters so much. Invest too little in your biggest winners, and they may barely move the needle. Invest too much in a risky position and one mistake can do serious damage.

A good coach understands this instinctively. Sometimes, you’ve got to be ruthless.

You don’t give every player the same number of minutes. Some deserve larger roles. Others are valuable in more limited situations. Sometimes a star who has already carried the team needs his workload reduced.

And if someone stops contributing, you eventually have to replace them.

A portfolio works the same way.

Your objective isn’t to maximize the amount of money you have in your favorite stock. It is to build the strongest overall portfolio.

Building the Roster

That idea has become especially important during the AI boom.

I, along with my InvestorPlace colleagues Luke Lango and Eric Fry, have spent years identifying opportunities in artificial intelligence. In fact, across our research, the three of us have issued 219 stock recommendations.

That creates a pretty nice problem. There is no shortage of ideas.

The harder question is deciding which ones actually deserve your investment dollars.

Now, you’re ultimately the only one who can determine that. But we want to give you tools to help. So, we recently went through our research and rebuilt the AI Revolution Portfolio from the ground up. Rather than handing subscribers another enormous list of recommendations, we narrowed our research down to 19 stocks that we believe deserve a place in the portfolio today.

But we didn’t stop there.

For the first time, every position comes with a recommended allocation percentage:

• Strong Buys: 1.5X allocation 
• Buys: 1X allocation 
• Holds: 0.5X allocation 

Each position is sized based on how we believe it fits into the larger portfolio. Those allocations are designed to balance opportunity against risk, prevent any one stock from dominating the strategy and make sure the individual pieces work together.

Think back to Popovich and Duncan. Tim Duncan was one of the greatest players in basketball history. But that didn’t mean Popovich had to play him 48 minutes every night.

Likewise, one of our favorite AI stocks can remain an excellent company without deserving an unlimited percentage of the portfolio.

And as conditions change, those roles can change too. A winner may grow into an outsized position and need to be trimmed. Fundamentals can deteriorate. Another company may present a better opportunity. Sometimes, a holding may simply stop fitting the way we want the portfolio constructed.

That’s why portfolio management is different from simply finding stocks.

Making the Math Easy

Of course, recommended percentages create another practical question: What does a recommended allocation actually mean for you?

That depends on how much money you have chosen to devote to the strategy.

So, we created the AI Revolution Position-Size Calculator.

You enter the total amount you’ve decided to allocate to the AI Revolution Portfolio. The calculator then applies our recommended allocation percentages and translates them into the number of shares to consider buying in each position.

You decide how much capital you want to put to work. We provide the portfolio blueprint. And the calculator does the arithmetic.

We’ve also recorded a special AI Revolution Portfolio Board Meeting, where Luke, Eric and I go through every position and explain why we own it, how it fits with the other holdings, what we’re watching and what could eventually cause us to sell or replace it.

In other words, we don’t simply show you the roster. We explain why each player is on it and the role we believe that player should have.

Manage the Team

The last time we significantly rebalanced the AI Revolution Portfolio, in December 2024, it went on to gain 58% through July 23. The NASDAQ gained 25% over the same period.

Past performance never guarantees future results, of course. But I think those results illustrate an important point.

Investing success isn’t always about finding one magical stock. It is about making a series of good decisions about what you own, what you don’t own and how much of your capital you put behind each idea.

That’s exactly what Popovich understood – and that’s why they were able to win one last championship together in 2014 before Duncan retired.

Because even when you have a legendary player, you still have to manage his role with the entire team in mind.

Again, we’ve had no shortage of amazing picks. For example, NVIDIA Corporation (NVDA) is one of my most famous calls. It’s up more than 4,700% since I initially recommended it. And in the AI Revolution Portfolio, it’s still in there.

But as far as we’ve come, I believe the AI Revolution still has a lot of room to run. And I want to maximize our chances of winning. So while you’ll still see stocks like this in the portfolio, there are also a lot of new, emerging stars that deserve your attention.

And I want to help you understand better how it should all fit together.

That’s exactly what Luke, Eric and I are trying to do with the newly rebuilt AI Revolution Portfolio. We’ve selected 19 AI opportunities we believe deserve a place on the roster today, assigned recommended allocations to each one and built a tool that makes putting those allocations into practice much easier.

The new portfolio is live right now.

Click here to watch our full presentation and see what we’ve put together.

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 Why Giving Your Best Stock Too Much “Playing Time” Can Cost You appeared first on InvestorPlace.

Rates will land wherever they land.

That’s what Paul Volcker, the Fed Board Chair in 1979, opined to reporters at a press conference the evening of Oct. 6, 1979.

The central bank, Volker noted, would stop steering interest rates and start choking the money supply instead.

Eventually, rates landed right on top of the American household like a piano in an ’80s cartoon.

By the fall of 1981, the average 30-year mortgage hit 18%, as housing starts collapsed to their weakest level post-World War II. Outraged homebuilders protested by sending sawed-off two-by-fours to the Fed’s front door. If you owned a home, a truck, or a tractor, those three years were some of the most brutal in modern American history.

Meanwhile, in an office park in Cupertino, California, a five-year-old company called Apple Inc. (AAPL) was having the best stretch of its young life.

Apple’s revenue surged from roughly $48 million in fiscal 1979 to $117 million in 1980 to $335 million in 1981; and in December 1980, Apple went public in the largest offering since Ford Motor (F) in 1956.

Chipmakers poured money into new fabs straight into the teeth of the worst credit market in half a century. Demand for silicon, it turned out, had almost nothing to do with the mortgage rates.

That same dynamic is happening today, and your portfolio depends on you reading it correctly.

The 10-year Treasury yield sits around 4.7%. The 30-year has pushed above 5.3% for the first time since 2007. Oil is grinding toward $90 a barrel. The tape has gone sour, and the market is treating all of it as one giant risk-off signal.

That’s the wrong outlook.

On this week’s macro episode of Being Exponential, I walk through why the ranges we are stuck in are the ranges the AI trade already survived — plus the one force that actually does end this boom, and it has nothing to do with yields. Watch it here:

The Bond Market Is Doing the Fed’s Dirty Work

The situation in the Middle East is not resolving. Meanwhile, Washington keeps escalating the economic pressure campaign on Iran, and oil has responded by grinding higher. That grind is a slow reassessment, the market quietly pricing out the assumption that a clean exit ramp exists.

Sticky oil means sticky inflation, call it high twos to low threes for the foreseeable future. Sticky inflation means the Fed cannot cut. And our Fed chair has no appetite for hiking either, because he was installed to do the opposite and has no interest in playing villain. So the bond market does the work for him, and the burden lands where it always lands.

Those long rates are your mortgage. Your auto financing. Your home equity line. For most American families, that is the bulk of monthly outflow, and when those payments stay high, discretionary spending stays low. Walmart Inc. (WMT) showed you exactly that in its latest quarter — the consumer is decelerating.

Higher for longer rates. Higher for longer oil. Lower for longer discretionary spending. The market has no reason to be thrilled about that combination.

Why This Is ‘Goldilocks Bad’

That macro backdrop is bad enough to squeeze the consumer, dent travel plans, and flatten retail comps. It is nowhere near bad enough to alter a multitrillion-dollar infrastructure buildout.

I call that Goldilocks bad, and it is the engine of the bifurcation thesis.

We have had a weak consumer since 2022. The stimulus checks ran dry, savings drained, and households have been under pressure through 2023, 2024, 2025, and into 2026. Across that entire stretch, hyperscaler capital spending plans never changed. Not once.

Look at the ranges. The 10-year has oscillated between 3.8% and 5% for two solid years. Oil traded as high as $120 and as low as $50. Capex plans did not move at either end of either range, because these budgets get set on five- to 10-year return horizons, and a quarterly sentiment survey does not enter the calculation.

So the risk factors spooking the tape are real. Their primary effect is to widen the gap between the AI economy and everything else.

The Levels That Would Change My Mind

The ten-year between roughly 4.5% and 5%. Thirty-year between 5% and roughly 5.4%. Oil in the $80s. Inside them, the AI infrastructure buildout has a demonstrated ability to keep working, because we have already watched it happen. Break above them, and the historical proof point disappears. That is the yellow flag.

I do not expect it, because you do not get a long-end yield spike with a consumer this fragile, job growth negative last month, and wage growth running below inflation. If something dramatic changes there, you reassess. As of today, the weight of evidence says what we have is what we are stuck with.

Jevons Is Winning, and the Numbers Keep Going Up

Meanwhile the good stuff stays good.

Bears point to collapsing token prices and call it commoditization. That is Jevons paradox playing out in real time. Cheaper compute pulls in far more compute usage, and volume has gone exponential. Anthropic and OpenAI both sit above $100 billion in annualized recurring revenue, growing 35% to 40% sequentially — from companies that barely sold anything to anyone three years ago.

Bloomberg’s revised 2027 hyperscaler spending estimate now runs north of $1 trillion. Two quarters ago, 2027 was penciled in around $800 to $900 billion, with the trillion-dollar mark not expected until 2028 or 2029. The estimates keep migrating up and to the right.

Anthropic is the standout, because it is growing faster than almost any company in modern capitalism and it recently turned profitable while doing it. Its IPO is expected in September, and one publicly traded vehicle offers pre-IPO exposure — a wildly volatile flyer I name on the podcast and recommend nowhere in our model portfolios. Treat it as a lottery ticket rather than a position.

The Shot Clock Nobody Is Watching

What kills this boom is legislation.

Pennsylvania just passed a law that will meaningfully slow data center construction. New York went further. Florida and California are drafting their own. You now have a genuine tug-of-war — a federal government pushing all-in for AI infrastructure and a growing bloc of states pushing back, from both parties.

That coalition lacks the votes to matter in the midterms. By 2028, it becomes the defining talking point of the presidential cycle, and I believe the populist side wins. A manufactured slowdown of the buildout is what eventually ends this trade.

If this is 1998 in dot-com terms, then 1999 and 2000 are still in front of us. There is real runway here. There is also a shot clock, and it is running.

Earnings are still climbing. Estimates are still climbing. The buildout is still happening. Yields sit below the levels at which this trade has already proven it works, and oil is uncomfortable for households while remaining perfectly workable for hyperscalers.

The rally is fatigued rather than finished. Own AI infrastructure. Stay careful with consumer-exposed names like Nike Inc. (NKE) and Walmart. And know which of the two economies on your screen you actually own.

The full macro episode of Being Exponential goes deeper on the yield ranges, the Anthropic IPO setup, and why I think bitcoin stays trapped in its dead zone until the Clarity Act vote resolves. Watch it here.

The Uncomfortable Truth

Knowing the macro backdrop is “Goldilocks bad” doesn’t tell you how much of your money should be in AI infrastructure versus how much should be sitting in cash waiting for a better entry on names like Walmart or Nike.

That’s a different question. And it’s the one Louis, Eric, and I have spent the past several weeks answering.

Between the three of us, we’ve published more than 200 buy recommendations over the past year alone. My own call on Lumentum (LITE) is up 645% since last August. Louis’ Nvidia (NVDA) position is up 375% since 2023. Individually, we’ve found some of the best AI winners of this entire boom.

But finding winners was never the hard part. The hard part — the part Wall Street pays portfolio managers up to $10 million a year to get right — is knowing how much to own, which names to hold alongside each other, and how the whole thing behaves when yields spike or oil grinds toward $90, exactly like they’re doing right now.

That’s why we rebuilt the AI Revolution Portfolio from the ground up, and why Louis has stepped into a new role to lead it. Since inception, the portfolio is up 106.7%. Since its last rebalance alone, it gained 58% through July, more than double the Nasdaq’s 25% over the same stretch.

The newly rebuilt portfolio is live now — roughly 20 stocks, each with a specific allocation percentage attached, so you’re not guessing how much to put where. It comes with our AI Revolution Position-Size Calculator, Eric’s new report on the AI stocks to sell before the next shakeout, my own report on the one stock I believe has true 100X potential in this Super Exponential environment, and a recorded Board Meeting where the three of us walk through every single position.

This is exactly the kind of environment the portfolio was built for… one where the AI trade and the consumer economy are telling two completely different stories, and where owning the right things in the right proportions matters more than any single pick.

Click here to access the AI Revolution Portfolio.

The post How to Stop Worrying About the Fed and Love the $2 Trillion Anthropic IPO appeared first on InvestorPlace.

In today’s Friday Digest takeaway, Eric argues that the flood of money into humanoid robotics points to a bigger, more durable opportunity than any single robot maker can capture. Every machine will need a brain, eyes, muscles, and joints – and the firms supplying those parts don’t have to guess which manufacturer ultimately wins. He points to one day this summer when investors first started pricing in that build-out, and what it did to a handful of component stocks.

Below, Eric also shows how this fits the rebuilt AI Revolution Portfolio that he assembled with Louis Navellier and Luke Lango – nearly 20 world-class AI stocks built as a holistic portfolio, each with a specific, deliberate allocation. Our experts went into detail about it earlier this week at a live event, which you can catch the free replay of right here.

Bottom line: While the race to build these robots will crown a few winners, the companies arming them all may be the safer investment bet.

I’ll let Eric take it from here.

Have a good evening,

Jeff Remsburg

Hello, Reader.

On August 16, 2009, Usain Bolt ran the 100-meter dash in 9.58 seconds at the World Athletics Championships in Berlin. The time set a new world record (and broke Bolt’s previous one).

Bolt’s record has stood for nearly two decades. No runner has managed to beat it.

That remains true… ish.

Because 17 years and 1 day after Bolt’s record-breaking sprint, Chinese robotics company Unitree Robotics unveiled a humanoid robot called “Superman.”  And the company claims it can run faster than “the fastest man on Earth.”

Superman reportedly reaches a top speed of 12.66 meters per second – faster than Bolt’s estimated peak speed of about 12.4 meters per second.

Unitree debuted Superman on X, in a post that went viral with over 1 million views. You can check it out below.

Unitree New Robot Preview: “Superman” Breaking the Limits of Humanity🥳
Standing high jump 2 m, top speed 12.66 m/s (0.85 m leg length)
Surpassing the standing high jump and running speed records of all humans around the world
This new machine has only been in development for a… pic.twitter.com/12i80ITU6p

Superman was a viral stunt to promote Unitree’s IPO, which came two days later, offering a timely glimpse into the market’s growing appetite for humanoid robotics.

So, in today’s Smart Money, I’ll show how that excitement points to something much bigger: As AI moves into the physical world, a whole new wave of investment opportunities could follow.

Let’s get off to the races…

The $50 Billion Robot Bet

Yesterday, the Hangzhou, China-based humanoid robot maker began trading on the Shanghai Stock Exchange’s STAR Market under the ticker 688836. And the results were a sprint right out of the blocks.

Shares were priced at 150.80 yuan but surged as much as 629% during the day, closing at 845 yuan – a 460% gain. That sent Unitree’s market value soaring to roughly $50 billion.

In other words, investors just put a multibillion-dollar price tag on the future of humanoid robotics.

But there is a catch. Commercial deployment of humanoid robots remains in its early stages. And the U.S.-China relationship could create another obstacle, with U.S. regulators moving to restrict imports of Chinese humanoid and four-legged robots on national-security grounds.

Still, those hurdles haven’t stopped investors from putting serious money behind the sector’s future.

Unitree’s IPO now gives investors a public valuation to use as a benchmark for the rest of the industry, especially as several other Chinese robotics companies – including Deep Robotics, Mech-Mind Robotics, and Leju Robotics – pursue listings of their own.

And that’s where the investment opportunity becomes much bigger than any single robot maker. The field is likely to get crowded, and Unitree’s IPO shows just how much investors are willing to pay for a stake in the winners.

So, the bigger opportunity may be in the companies supplying the brains, eyes, muscles, and joints that these machines need.

Betting on the Supply Chain

As humanoid robot production takes off, somebody has to supply every robot with dozens of motors, sensors, actuators, gears, and chips. And there are four things every successful humanoid robot will need:

• Brain: AI processors and software.
• Eyes: cameras, lidar, and other sensors.
• Muscles: motors and motion-control systems.
• Joints: precision gears, bearings, and other components that allow all those parts to move.

These are the picks-and-shovels plays in the physical AI opportunity. And we’ve already seen what can happen when investors start betting on that supply chain.

On July 1, optimism around physical AI drove a rally in component stocks. Investors were looking ahead to a potential humanoid production ramp – particularly around Tesla Corp.’s (TSLA) Optimus program – alongside other company-specific catalysts.

As a result, shares of companies tied to the humanoid-robot supply chain surged as investors looked beyond the robot makers themselves and toward the companies supplying their components.

Ambarella Inc. (AMBA), a “brain” supplier, jumped 28%. Ouster Inc. (OUST) and Cognex Corp.(CGNX), which supply “eyes,” gained 15.6% and 5.9%, respectively. Regal Rexnord Corp. (RRX), the “muscles,” jumped 8.3%. And Harmonic Drive Systems Inc. (HSYDF), the “joints,” rallied 13.1%.

That’s the advantage of the picks-and-shovels approach. Component suppliers can potentially sell to multiple robot manufacturers, meaning they don’t have to predict whether Tesla, Unitree, or another company ultimately wins.

One Race, Many Winners

At the start of a 100-meter race, you could spend your time trying to predict whether anyone will ever beat Usain Bolt’s record. Or you could profit from everything happening on the track.

The AI Revolution is increasingly looking like that kind of race.

There are hundreds of companies sprinting toward the future, and the challenge isn’t simply finding one AI winner. It’s figuring out which opportunities deserve a place in your portfolio, how much to allocate to each one, and how those investments fit together.

That’s exactly why my colleagues Louis Navellier, Luke Lango, and I have gone back through our years of AI research and rebuilt the AI Revolution Portfolio.

We’ve narrowed a huge universe of AI opportunities down to roughly 20 positions – including the companies we believe are best positioned to benefit from the AI Revolution and the infrastructure behind it.

And we’re not just handing you a list of ticker symbols. Each position comes with a specific allocation, giving you a blueprint for how we believe these opportunities should work together.

The last time we did this, our AI Revolution Portfolio gained 58% from its December 2024 rebalance through July 23 – more than twice the Nasdaq’s 25% gain over the same period.

Now, we’re doing it again. And the newly rebuilt AI Revolution Portfolio is live today.

Click here to learn more.

Regards,

Eric Fry

The post The Robot IPO Everyone’s Talking About (and the Stocks Nobody Is) appeared first on InvestorPlace.

But the people who lived there had other ideas.

At the time, America was in the middle of a massive infrastructure boom. President Dwight D. Eisenhower had launched a bold plan to build a nationwide system of interstate highways.

Cities across the country were being asked to make way for them.

That didn’t sit too well with a lot of folks in San Francisco.

So, they fought back. And they kept fighting for years.

They packed public meetings, signed petitions and protested.

^{Source: San Francisco Chronicle}

By 1966, two of the biggest remaining freeway proposals were defeated by a narrow margin. After nearly a decade of fighting, they succeeded in stopping major freeway projects from cutting through San Francisco.

Now, here’s the important part…

San Francisco may have stopped those freeways from being built in its backyard. But it didn’t stop America’s highway boom. Not even close.

The Interstate Highway System continued expanding across the country for decades.

Folks, that’s worth remembering today. Because nearly 70 years later, we’re watching a very similar fight play out again.

Communities across the country are pushing back against new data center projects. They’re concerned about electricity costs, water usage, noise and strain on local power grids.

The pushback has gained a lot of momentum. And I’ve received a few emails from investors wondering whether America’s massive data center boom is finally hitting a wall.

So, in today’s Market 360, let’s take a closer look at the growing pushback against data centers. We’ll talk about why I don’t think it will derail the massive buildout underway – and why there’s more to profiting from the AI boom than simply picking a few good stocks.

When Pushback Becomes Policy

We see stories about packed town halls and data center projects on local news stations across the country.

And the calls from citizens have gotten loud enough that the politicians are responding.

Local officials are responding with temporary moratoriums on new data center construction.

In fact, Interconnected Capital has a data center moratorium tracker that shows just how widespread these restrictions have become. All told, they’re counting about 268 moratoriums of some kind across the country.

New York recently became the first state to institute a statewide moratorium on large data centers. This restricts both the construction of and permits for hyperscale data centers that consume 50+ megawatts of power. The moratorium is in effect for one year.

The one-year moratorium was enacted to give New York the time to refine its regulations. New York Governor Kathy Hochul wants all new data centers to be subject to the same “consistent standards.”

The state plans to review and research the environmental impact of data center construction and operation. Once standards are agreed upon, the moratorium will end.

Upstate New York remains attractive for data centers thanks to abundant hydropower and its proximity to major Canadian hydroelectric resources.

So, I suspect construction will resume once these standards are set.

The Boom Is Still Intact

In the meantime, we need to remember that the data center boom continues relatively unabated nationally.

Yes, there has been some pushback from communities across the country. Some of it is warranted. But the reality is that the number of data centers in the U.S. is still set to nearly double.

According to Stanford University’s AI Index Report, there were 5,427 data centers in the U.S. at the end of 2025. There are plans to add 3,969 new data centers – 802 of which are currently under construction. Data center construction rose 7% in June to $68.3 billion, which represented a 46% year-over-year increase.

By my calculations, the order backlog for data centers will persist through 2029 to 2030.

So, please ignore all the fear-mongering headlines about the data center boom somehow coming to an abrupt end.

For example, I’ve had readers email me about articles in the mainstream media claiming that nearly half of all the data centers planned for 2026 have been delayed or canceled.

That stat is real, but it’s less alarming than it sounds for two reasons.

First, of course, there are delays – that’s exactly what happens when an industry is booming faster than its supply chains can keep up!

Data center construction is being held back by shortages of turbines, transformers, skilled labor and power itself, not because demand dried up. If anything, delays like these are a sign of just how hot this boom really is.

Second, a lot of these “planned” projects were never as real as the headlines suggest.

Most of these estimates count a project the moment it’s announced – a press release, a real estate filing, sometimes just a non-binding letter of intent – none of which guarantees the project ever gets built.

Take Texas, for example.

The state has its own grid. And the grid operator is currently fielding more than 410 gigawatts of data center interconnection requests. The problem is, the entire state’s peak power demand is only about 85 gigawatts. That queue is nearly five times the size of the whole grid!

So, a lot of that is speculative filing that’s padding the numbers. Some of it may, in fact, never break ground. Some individual projects will genuinely get delayed or shelved.

But the overall data center boom remains fully intact.

Profiting From What Comes Next

As we saw in San Francisco, local opposition doesn’t necessarily stop a nationwide infrastructure boom.

And I think the same thing is true for data centers today.

The bottom line is that this is a big country. There is plenty of room to build these things.

And the flow of money being invested into these projects isn’t stopping, either.

In fact, Goldman Sachs forecasts a total of $1 trillion in global AI-related investment for 2026.

They also project the cumulative spend AI infrastructure and data centers will top $5 trillion to $7.6 trillion by 2030–2031.

That means there’s also still plenty of opportunities to profit from the buildout.

Most of my followers already know this. That’s because one of the top searches I’m seeing on my new Stock Grader AI tool (subscription required) right now is for A-rated stocks in the technology sector. I’m also getting tons of questions about the top AI infrastructure plays.

I understand why. There are many companies that stand to benefit as the AI and data center buildout continues. In fact, my InvestorPlace colleagues Luke Lango and Eric Fry, along with me, have made more than 200 recommendations related to the AI Revolution over the years.

But here’s the thing…

Picking a few great AI stocks is only part of the equation.

You also need to know how much to invest in each one, how those positions fit together and whether your portfolio is taking on too much risk in one area.

That’s exactly what I’ve been working on for the past few months.

Together, we’ve taken a fresh look at our AI Revolution Portfolio and how we can make it even more useful to investors.

We’ve already seen what this approach can accomplish. Following our last major rebalance in December 2024, the AI Revolution Portfolio gained 58% through July 23 – more than twice the Nasdaq’s 25% return over the same period.

And now, we’ve rebuilt it again…

Only this time, for each position, we’re now providing a recommended allocation with the help of our new Position-Size Calculator tool. This should help give you a clearer blueprint for putting those recommendations into action.

Earlier this week, Luke, Eric and I went on camera to explain what we’re doing, how the portfolio works and why we believe this approach can help you position yourself better as the AI Revolution continues.

You can watch the full presentation here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Why Data Center Moratoriums Won’t Derail the $7 Trillion AI Boom 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 were able to ride the energy supercycle that followed to generational wealth.

Today’s chokepoint is rare earth magnets.

The weapon has already been test-fired and the regulatory clock is ticking toward January 2027.

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.

Rare earth magnets are just one piece of a much bigger puzzle, though. Finding the picks-and-shovels play behind the next industrial shift is exactly the kind of hunting that led me to Lumentum (LITE) last August – a stock that’s up 645% since. My colleague Louis Navellier found the same kind of setup in Nvidia (NVDA) back in July 2023. It’s up 375% since.

But there are now more promising AI-and-AI-adjacent opportunities – robots, rare earths, chips, power, data centers – than any one investor could reasonably track.

Between the three of us, Louis, Eric Fry, and I put out more than 200 AI recommendations over the past year alone. That’s a lot of data, but having those stocks on face value isn’t the same as insight.

So we did something about it.

We just finished rebuilding our AI Revolution Portfolio from the ground up – about 20 stocks, pulled from across our combined research, each with its own recommended allocation. Since its last rebalance, the portfolio is up 58% through July 23 – more than double the Nasdaq’s 25% gain over the same stretch.

It’s live now. And it’s the clearest answer I can give you is not just which companies matter, but how much of each to own, and how the pieces fit together.

Don’t wait for the gas lines to form…

Watch the full AI Revolution Portfolio replay before it closes Tuesday, August 25.

The post The Reason China Targeted MP Materials Might Shock You appeared first on InvestorPlace.

Yesterday, a Chinese robot maker delivered one of the wildest market debuts in recent memory.

Shares of Unitree Robotics – the Hangzhou-based company whose backflipping, kung-fu-fighting humanoids have racked up tens of millions of views online – closed their first trading session up about 460%. The offering was oversubscribed more than 8,000 times.

But the underlying bet here isn’t on Unitree, it’s on the single biggest technological leap since the smartphone – the moment AI stops living in a chatbot and steps into a body.

For three years, the AI boom has played out on screens – text, images, code. The next phase gives that intelligence arms, legs, and hands, then turns it loose on the physical world. It will be the most consequential step in our economic evolution since the assembly line – and Wall Street is only beginning to price it.

The numbers related to what’s coming are staggering…

Morgan Stanley pegs the humanoid market at $5 trillion by 2050, with a robot workforce north of 1 billion units – rivaling India’s entire working-age population. Citibank thinks it could reach $7 trillion. And Elon Musk, never shy, calls Tesla’s (TSLA) humanoid “Optimus” potentially “the biggest product of all time.” He pegs its long-term revenue at $10 trillion and estimates eventual demand “in excess of 20 billion units.”

Tesla has already ripped out the Model S and Model X lines at its Fremont plant to make room for robots, and now describes itself, flatly, as a “physical AI company.”

So, the prize is almost unimaginably large. Which brings us to the problem…

Every one of these machines – Unitree’s, Tesla’s, all of them – depends on one ingredient that America’s chief rival controls

That’s the dynamic our technology expert Luke Lango, editor of Innovation Investor, has been researching for months. In a recent piece highlighting this research, he opens with a history lesson.

In October 1973, Arab oil producers slapped an embargo on the United States. Prices quadrupled almost overnight. Gas lines stretched for blocks. Washington imposed a national 55-mph speed limit to ration fuel – and the shock helped kick off a decade of stagflation.

As Luke notes:

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.

With robotics/humanoids, the chokepoint isn’t oil. It’s rare earth magnets – chiefly neodymium-iron-boron – that are packed inside every electric motor.

A single humanoid can carry dozens of those motors in its shoulders, wrists, hips and ankles, adding up to two to four kilograms of rare earth magnets per machine, sometimes more than an entire electric vehicle (EV). More robots means more motors… more motors means more magnets… and the supply sits almost entirely in China’s hands.

China produces roughly 90% of the world’s finished rare earth magnets, and it has already flexed that leverage – restricting exports during this year’s tariff standoff and blacklisting U.S. firms.

Washington has finally woken up, pouring billions into a domestic supply chain. Plus, defense rules now require contractors to phase out Chinese magnets by January 2027.

So, which companies will benefit from this push?

That’s a trillion-dollar question with one name high on the list – MP Materials (MP), the one U.S. company that can mine, refine, and turn rare earths into finished magnets at scale.

The Pentagon has taken a 15% stake, and Apple (AAPL) and General Motors (GM) have both signed magnet supply deals. The reason why is simple. As Luke puts it, “whoever supplies the magnets supplies the empire.”

But MP isn’t the only stock that’s poised to benefit here.  I want to cover more ground in today’s Digest, but for a much deeper dive – plus a free, related stock pick from Luke – he’s just released his latest research brief called XPANSE. If yesterday’s Unitree fireworks and the potential market size of robotics have your attention, I encourage you to give Luke’s research a look.

The shape of the American consumer

Want to know how the American consumer is really doing? Watch what they’ll still spend on – and what they won’t.

This morning gave us the broadest read of all. Walmart (WMT), arguably the single best gauge of the American wallet, reported before the bell. Sales beat expectations, rising 5.9% to $187.9 billion – and yet the stock is down nearly 10% as I write.

The issue was the quality of the beat. It leaned on a nearly $3 billion tariff-refund benefit rather than real demand. Organic U.S. sales growth slowed, and management pointed to shoppers making “trade-offs” as higher prices and fuel costs bite.

That word – trade-offs – is a good description of what we’re seeing today on Main Street. The American consumer isn’t collapsing. But they’re choosing carefully: spending on what they must and deferring what they can.

And you could see those exact trade-offs earlier this week, in the two housing-related names that reported ahead of Walmart.

On Tuesday, Home Depot (HD) reported that sales rose 5.7% to $47.9 billion, while comparable sales grew 1.7%, beating expectations and reaffirming its guidance. Solid enough. But the color from management was more interesting than the numbers.

CFO Richard McPhail told CNBC that Home Depot is still operating in “frozen housing market conditions.” He described his customer as “a healthy cohort” – but admitted shoppers still haven’t returned to big-ticket projects. So, growth is coming from smaller jobs. The average transaction crept up 2.8%, even as the number of transactions slipped.

Lowe’s (LOW) reported yesterday. Sales climbed 8.3% to $26 billion, and comps eked out a 0.2% gain – the fifth straight quarter of positive comps. But the company missed on revenue and trimmed its full-year outlook to the bottom of its range.

The dynamics beneath the top-line numbers are the whole story. Here’s CEO Marvin Ellison:

Sustained growth in Pro, Online and Home Services led to our fifth consecutive quarter of positive comp sales, despite pressure in discretionary DIY spending.

There it is again – Pros and non-negotiable repairs are holding up. But discretionary do-it-yourself spending – the new kitchen, the bathroom remodel, the deck – is slow. Same trade-off, same cautious consumer: spend where you must, wait where you can.

We’re seeing this same “slowdown” dynamic bleed into new construction. Earlier this week, we learned that July housing starts cratered 12.4%, with single-family building falling to its slowest pace since November 2022.

Source: Fed data

Legendary investor Louis Navellier, editor of Growth Investor, flagged that number in Tuesday’s Flash Alert podcast:

The July housing starts fell 12.4%. They’re running only at $1.24 million annual pace.

This is just a sign what higher interest rates do. Hurts the housing market, hurts anything that’s interest-rate sensitive.

So, the view from Main Street is shaky: a cautious consumer and a housing market frozen solid – which makes what I recently read from Senior Analyst Brian Hunt even more interesting…

Is it time to buy housing-related stocks anyway?

Brian, editor of Money & Megatrends, has been urging his readers to recognize a setup brewing in certain housing-related stocks – despite questionable macro data.

In his August 3^rd issue, he wrote something that every investor should remember for as long as they’re in the market:

The stock market is the world’s greatest forecasting mechanism. It tends to look ahead 6-12 months.

When an industry is in a recession, its stock prices will rise before the news media announces it is recovering. When an industry seems to be doing well, its stock prices will decline before the news covers its downturn.

This is often called “discounting” or “pricing in” the future.

What this means for investors is important – by the time the headlines confirm a housing recovery, the easy money will already have been made. The stocks move first. And in recent months, a basket of housing-related stocks has been moving.

A few weeks ago, Brian flagged a cluster of beaten-down housing-materials names that were quietly breaking out to multi-month highs – decking maker Trex (TREX), paint giant Sherwin-Williams (SHW), and insulation heavyweight Owens Corning (OC) among them.

Here’s Brian:

These economically sensitive firms are important “real world” indicators. They almost always do a better job of telling us what is happening in the economy than any media outlet or economist.

So, how do we square Brian with Louis, who just warned that higher rates are hurting anything interest-rate sensitive?

Easy – they’re watching different clocks. Louis is describing the pain right now, in today’s economy. Brian is reading what the market believes about the economy a year from now. Both can be right. And that gap between the grim present and the hopeful tape is exactly where forward-looking investors go hunting.

There’s a neat symmetry here, too…

Many of the materials companies Brian is watching are the same ones stacked on the shelves at Home Depot and Lowe’s – where Pro work and everyday repairs are holding the floor even as big discretionary projects stay frozen.

Here’s Brian’s overall take:

Can we start making money in the residential home business again?

The new, strong price action in many leading homebuilding materials and equipment suppliers implies that the answer to those questions is “YES.”

Bottom line: When stocks begin making multi-month highs in the face of underwhelming macro data, it’s worth noticing.

One last thing that brings us full circle

We opened today on the next chapter of the AI boom: intelligence stepping out of the chatbot and into a physical body. Let’s close on the boom itself.

Yesterday, our three AI heavyweights –Luke, Louis, and Eric Fry of Fry’s Investment Report – went public with a project they’ve been working on behind the scenes for months: a ground-up rebuild of their AI Revolution Portfolio.

The reason for the rebuild is simple…

Over the past year alone, these three experts have issued dozens of AI-related recommendations. That’s a lot of winners – but it’s also a problem. Which ones do you buy? How much goes in each? How do they fit together? And what are the top picks starting today, looking forward?

Owning the right AI companies, it turns out, is only half the battle. Rubber-meets-road implementation is a huge factor.

So, Louis, Luke, and Eric went back through their entire universe of AI research and distilled it down to a small, hand-picked basket of their highest-conviction ideas – each with a recommended allocation. Not just what to buy, but how to build it.

There’s a personal headline here, too. After 47 years, Louis is changing his role. I won’t give away those specifics – it’s in the free replay of yesterday’s presentation – but it’s significant.

If you missed it, the replay is up and available for a limited time. You can check it right here.

We’ll keep you updated on all these stories here in the Digest.

Have a good evening,

Jeff Remsburg

(Disclosure: I own AAPL, WMT, HD.)

The post Who Really Controls the $7 Trillion Robot Boom? appeared first on InvestorPlace.

Despite the name, you don’t give up your queen. You offer a pawn, accepting a little risk early in exchange for something potentially far more valuable: control of the center of the board.

Here’s what the setup looks like…

(Credit: chess.com)

It’s a strategy that has been used at the highest levels of chess for generations. Garry Kasparov, one of the greatest players in the history of chess, repeatedly battled through Queen’s Gambit positions during his legendary World Championship matches with Anatoly Karpov.

Lately, I’ve been wondering whether Jensen Huang is playing his own version of the Queen’s Gambit at NVIDIA Corporation (NVDA).

For years, Huang has been willing to put billions of dollars of NVIDIA’s capital at risk across the AI ecosystem. NVIDIA has put roughly $30 billion into OpenAI. It has invested billions in CoreWeave, Inc. (CRWV), Nebius Group N.V. (NBIS), Marvell Technology, Inc. (MRVL), Synopsys, Inc. (SNPS), Coherent Corp. (COHR), Lumentum Holdings Inc. (LITE), IREN Limited (IREN) and Corning, Inc. (GLW) – many of which turn around and spend heavily on NVIDIA’s GPUs and infrastructure.

It also owns major stakes in Intel Corp. (INTC) and Space Exploration Technologies Corp. (SPCX).

Critics have a name for that: “circular financing.”

Their argument is straightforward. NVIDIA gives money to AI companies. Those companies use some of that money to buy NVIDIA products. NVIDIA books the revenue, makes more money and invests even more back into the ecosystem.

Looked at one way, that can seem dangerously self-reinforcing.

However, I think Huang may have been sacrificing a few pawns to gain control of the center of the AI board.

And now he’s made two moves that could change the game entirely.

So, in today’s Market 360, let’s look at how Huang’s Queen’s Gambit has worked so far… the two new moves that could tighten NVIDIA’s grip on the AI economy… and whether the king of AI is getting closer to checkmate.

The Gambit

First, it helps to understand just how aggressive NVIDIA has become as an investor.

Between 2021 and 2025, NVIDIA participated in 283 funding rounds involving 241 different companies. Nearly 85% of them were AI startups.

Its investments now stretch across nearly every layer of the AI ecosystem.

The strategy is fairly easy to understand.

AI companies need extraordinary amounts of computing power. But GPUs, data centers, networking equipment and power infrastructure are extremely expensive. Younger companies in particular may not have enough capital to build everything they need.

So, NVIDIA helps provide it.

That capital allows these companies to expand their AI infrastructure. And much of that infrastructure, naturally, runs on NVIDIA technology.

Critics argue that this creates a circular system.

NVIDIA invests money in a company. The company buys NVIDIA GPUs. NVIDIA generates more revenue. And NVIDIA can then invest even more money across the AI ecosystem.

I understand why that makes some investors nervous.

If AI spending eventually slows sharply, NVIDIA could feel the impact twice – first through weaker demand for its core products and again through falling values across the companies and projects it has financed.

But there is another side to this strategy.

Every dollar NVIDIA invests can help remove one of the biggest bottlenecks facing the AI boom: access to compute.

And every new data center built around NVIDIA hardware makes its ecosystem a little harder to displace.

That’s the gambit.

Huang is accepting additional financial exposure in exchange for greater control of the center of the AI economy.

And now he appears to be taking that strategy to another level.

Is “Checkmate” on the Horizon?

The first major move came on August 10.

NVIDIA announced agreements with Apollo Global Management, Inc. (APO), BlackRock, Inc. (BLK), Blackstone Inc. (BX), Brookfield Corporation (BN), Goldman Sachs Group, Inc. (GS) and KKR & Co., Inc. (KKR) to establish independent financing platforms designed to mobilize more than $500 billion of third-party capital for AI infrastructure.

Think about what Huang is doing here.

Instead of NVIDIA having to provide all the money required to keep the AI buildout moving, some of the largest pools of capital on Wall Street can help finance it.

The platforms are designed to fund GPUs, data centers, networking equipment, power infrastructure and other components needed by hyperscalers, AI labs and enterprises. NVIDIA itself describes the goal as turning AI compute into an “investable asset class” for global capital.

And NVIDIA still gets to sell the hardware.

That alone strikes me as a very clever answer to the circular-financing criticism.

If Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR are willing to put outside capital behind these projects, it becomes harder to argue that NVIDIA is simply manufacturing demand by financing its own customers.

But then Huang made another move.

On Monday, NVIDIA announced a major new arrangement involving OpenAI and SB Energy (owned by Softbank) at the PORTS-Pike Technology Campus in Ohio.

OpenAI has agreed to use roughly 8 gigawatts of computing capacity at the campus under a 20-year lease. And every bit of that AI compute infrastructure will run exclusively on NVIDIA technology.

NVIDIA, meanwhile, is investing $1.5 billion in SB Energy and providing credit support for the land, power and shell infrastructure needed for the initial 4.25 gigawatts of capacity. NVIDIA also has an option tied to the remaining 3.75 gigawatts.

This deal certainly won’t silence every circular-financing critic. NVIDIA is still putting capital at risk to help secure infrastructure for one of its biggest customers.

But let’s look at the whole board Huang is creating.

OpenAI gets the computing capacity it needs. SB Energy builds and operates the data center. Wall Street and infrastructure investors increasingly provide the capital.

And NVIDIA supplies the GPUs, CPUs, networking and full-stack systems at the center of it all.

That’s why I’m reluctant to dismiss these deals as simple financial engineering.

Huang may be building something much larger.

For years, NVIDIA has been the arms merchant of the AI Revolution.

Now it is helping build the financial system that allows its customers to keep buying the arms.

I wouldn’t call checkmate just yet. There are still plenty of pieces on the board, including Advanced Micro Devices, Inc. (AMD), Alphabet, Inc.’s (GOOG) custom chips and a growing number of companies developing their own AI silicon.

But Huang is making it increasingly difficult to compete with NVIDIA on chips alone.

You may now have to compete with its software. Its networking. Its enormous installed base. Its relationships throughout the AI ecosystem.

And increasingly, the financing infrastructure surrounding all of it.

That is a formidable position, folks.

The Next Move for AI Investors

I’ve been bullish on NVIDIA for years, and that hasn’t changed.

The stock has made my subscribers a tremendous amount of money, and I continue to believe NVIDIA is one of the premier companies of the AI Revolution.

But there’s an important lesson in Huang’s strategy for individual investors, too.

Chess isn’t won simply by having the most powerful piece on the board. It’s won by understanding how all the pieces work together.

And that’s becoming increasingly important for investors as well.

That’s why my special event yesterday with my InvestorPlace colleagues Luke Lango and Eric Fry was so important.

See, Luke, Eric and I have identified a tremendous number of opportunities throughout this AI Revolution. Over the past year alone, we’ve collectively issued more than 200 recommendations.

But here’s what’s different now.

We’ve taken the very best of those ideas — the highest-conviction, most powerful opportunities across all three of our research teams — and built something new: a concentrated portfolio of just 19 positions.

Just 19 of what we believe are the absolute best AI and technology opportunities available today.

Think of it as applying the principles of chess to investing – where every position has a purpose, and every holding is chosen because it strengthens the whole board.

See where I’m going with this?

The challenge now isn’t simply finding another AI stock we like. It’s figuring out which opportunities deserve your money, how much belongs in each one and how all those investments should fit together.

That’s a major reason why, after 47 years, I’m making the biggest change to my role at InvestorPlace in decades.

During our special event, I sat down with Luke and Eric to explain exactly what’s changing – and how we plan to approach the AI opportunity differently from here.

I’m not retiring. But I’ve come to believe that finding great stocks is only one part of the job.

Click here to watch the replay.

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), Advanced Micro Devices, Inc. (AMD), Coherent Corp. (COHR) and NVIDIA Corporation (NVDA)

The post What NVIDIA’s $500 Billion “Checkmate” Means for Investors appeared first on InvestorPlace.

On August 16, 2009, Usain Bolt ran the 100-meter dash in 9.58 seconds at the World Athletics Championships in Berlin. The time set a new world record (and broke Bolt’s previous one).

Bolt’s record has stood for nearly two decades. No runner has managed to beat it.

That remains true… ish.

Because 17 years and 1 day after Bolt’s record-breaking sprint, Chinese robotics company Unitree Robotics unveiled a humanoid robot called “Superman.”  And the company claims it can run faster than “the fastest man on Earth.”

Superman reportedly reaches a top speed of 12.66 meters per second – faster than Bolt’s estimated peak speed of about 12.4 meters per second.

Unitree debuted Superman on X, in a post that went viral with over 1 million views. You can check it out below.

Unitree New Robot Preview: “Superman” Breaking the Limits of Humanity🥳
Standing high jump 2 m, top speed 12.66 m/s (0.85 m leg length)
Surpassing the standing high jump and running speed records of all humans around the world
This new machine has only been in development for a… pic.twitter.com/12i80ITU6p

Superman was a viral stunt to promote Unitree’s IPO, which came two days later, offering a timely glimpse into the market’s growing appetite for humanoid robotics.

So, in today’s Smart Money, I’ll show how that excitement points to something much bigger: As AI moves into the physical world, a whole new wave of investment opportunities could follow.

Let’s get off to the races…

The $50 Billion Robot Bet

Yesterday, the Hangzhou, China-based humanoid robot maker began trading on the Shanghai Stock Exchange’s STAR Market under the ticker 688836. And the results were a sprint right out of the blocks.

Shares were priced at 150.80 yuan but surged as much as 629% during the day, closing at 845 yuan – a 460% gain. That sent Unitree’s market value soaring to roughly $50 billion.

In other words, investors just put a multibillion-dollar price tag on the future of humanoid robotics.

But there is a catch. Commercial deployment of humanoid robots remains in its early stages. And the U.S.-China relationship could create another obstacle, with U.S. regulators moving to restrict imports of Chinese humanoid and four-legged robots on national-security grounds.

Still, those hurdles haven’t stopped investors from putting serious money behind the sector’s future.

Unitree’s IPO now gives investors a public valuation to use as a benchmark for the rest of the industry, especially as several other Chinese robotics companies – including Deep Robotics, Mech-Mind Robotics, and Leju Robotics – pursue listings of their own.

And that’s where the investment opportunity becomes much bigger than any single robot maker. The field is likely to get crowded, and Unitree’s IPO shows just how much investors are willing to pay for a stake in the winners.

So, the bigger opportunity may be in the companies supplying the brains, eyes, muscles, and joints that these machines need.

Betting on the Supply Chain

As humanoid robot production takes off, somebody has to supply every robot with dozens of motors, sensors, actuators, gears, and chips. And there are four things every successful humanoid robot will need:

• Brain: AI processors and software.
• Eyes: cameras, lidar, and other sensors.
• Muscles: motors and motion-control systems.
• Joints: precision gears, bearings, and other components that allow all those parts to move.

These are the picks-and-shovels plays in the physical AI opportunity. And we’ve already seen what can happen when investors start betting on that supply chain.

On July 1, optimism around physical AI drove a rally in component stocks. Investors were looking ahead to a potential humanoid production ramp – particularly around Tesla Corp.’s (TSLA) Optimus program – alongside other company-specific catalysts.

As a result, shares of companies tied to the humanoid-robot supply chain surged as investors looked beyond the robot makers themselves and toward the companies supplying their components.

Ambarella Inc. (AMBA), a “brain” supplier, jumped 28%. Ouster Inc. (OUST) and Cognex Corp.(CGNX), which supply “eyes,” gained 15.6% and 5.9%, respectively. Regal Rexnord Corp. (RRX), the “muscles,” jumped 8.3%. And Harmonic Drive Systems Inc. (HSYDF), the “joints,” rallied 13.1%.

That’s the advantage of the picks-and-shovels approach. Component suppliers can potentially sell to multiple robot manufacturers, meaning they don’t have to predict whether Tesla, Unitree, or another company ultimately wins.

One Race, Many Winners

At the start of a 100-meter race, you could spend your time trying to predict whether anyone will ever beat Usain Bolt’s record. Or you could profit from everything happening on the track.

The AI Revolution is increasingly looking like that kind of race.

There are hundreds of companies sprinting toward the future, and the challenge isn’t simply finding one AI winner. It’s figuring out which opportunities deserve a place in your portfolio, how much to allocate to each one, and how those investments fit together.

That’s exactly why my colleagues Louis Navellier, Luke Lango, and I have gone back through our years of AI research and rebuilt the AI Revolution Portfolio.

We’ve narrowed a huge universe of AI opportunities down to roughly 20 positions – including the companies we believe are best positioned to benefit from the AI Revolution and the infrastructure behind it.

And we’re not just handing you a list of ticker symbols. Each position comes with a specific allocation, giving you a blueprint for how we believe these opportunities should work together.

The last time we did this, our AI Revolution Portfolio gained 58% from its December 2024 rebalance through July 23 – more than twice the Nasdaq’s 25% gain over the same period.

Now, we’re doing it again. And the newly rebuilt AI Revolution Portfolio is live today.

Click here to learn more.

Regards,

Eric Fry

The post Usain Bolt Just Got an AI Rival – Meet the Stocks Behind It appeared first on InvestorPlace.

Editor’s note: “The Most Important Part of Unitree’s IPO Wasn’t the Robot” was previously published in July 2026 with the title “The Physical AI Proof Points Are Suddenly Everywhere.” It has since been updated to include the most relevant information available.

When trading began on August 19, Unitree Robotics was a roughly $9 billion company. By the closing bell, investors had turned it into a $50 billion one.

Shares of the Chinese humanoid-robot maker finished their Shanghai debut 460% above the IPO price after climbing as much as 629% during the session.

That is probably too much, too fast.

Many humanoid robots still spend more time performing demonstrations than doing valuable work inside homes and factories. One blockbuster IPO does not settle the commercial case for the entire industry.

But the market’s message is hard to miss.

Physical AI has moved from the demo reel into the public markets.

For the first phase of the AI boom, intelligence mostly lived behind a screen. You typed a prompt. A model answered. Maybe it wrote code, summarized a document, generated an image, or helped draft an email.

Now AI is moving into machines that can see, hear, navigate, and act in the world around us.

AI is getting a body.

And public markets just put a price on it.

Unitree Is Only One Signal in the Physical AI Boom

Unitree’s debut is the loudest signal yet, but it is not happening in a vacuum. 

Across the Physical AI market, products are shipping, developer tools are opening up, and companies are building the supply chains required to scale. 

• Microsoft’s (MSFT) new Surface AI laptops, powered by Qualcomm’s (QCOM) Snapdragon X2 chips, are now shipping. On-device AI has moved from the roadmap into real products and enterprise budgets.
• Nvidia (NVDA) and Hugging Face are bringing robotics models, teleoperation tools, datasets, and workflows into LeRobot, giving developers a more open toolkit for building Physical AI.
• 1X unveiled a new hand for its NEO humanoid robot that is designed to grip, adjust, and manipulate objects more like a human hand. Useful robots need more than the ability to walk. They need to handle real-world objects reliably.
• Applied Materials (AMAT) and EssilorLuxottica are developing intelligent optical systems for AR and AI-powered eyewear, showing that the smart-glasses supply chain is beginning to industrialize.
• Mobileye (MBLY) is moving from autonomy supplier to robotaxi operator, with a planned U.S. launch in 2027 and a target of roughly 17,000 vehicles over the following five years.

These developments are starting to reinforce one another. Better tools speed up development, while real product launches give suppliers a reason to build for scale.

Physical AI is beginning to move like a real market.

What Physical AI Is – and Why It Needs a Different Hardware Stack 

Physical AI changes where intelligence has to run.

Cloud models can draw on vast data centers and send an answer back over the internet. A robot, car, wearable, or factory system has to make many decisions on the spot – often in milliseconds, on a tight power budget, and sometimes without a reliable connection.

That creates a very different hardware problem.

Your headphones need to filter background noise before you notice it.

A warehouse robot has to identify the right box and decide how to grip it.

An autonomous vehicle has to recognize a pedestrian and react immediately.

Those systems need fast local chips, sensors, memory, optics, power management, and connectivity working together.

That difference runs through the entire supply chain.

Six Types of Physical AI Stocks to Watch

Think of Physical AI not as a single industry but as six distinct hardware categories that all need to scale simultaneously. 

1. Edge AI Chips: Running Intelligence Locally

This is the foundation. Every physical AI device needs a chip that can run inference locally – fast, cool, and cheap. Qualcomm’s Snapdragon X2 is now shipping inside Microsoft’s Surface lineup. On-device AI has moved from the roadmap into products businesses can actually buy.

Arm‘s (ARM) architectures dominate mobile computing and increasingly sit inside processors designed for edge AI. Nvidia (NVDA) is pushing into embedded inference with its Jetson platform. AMD (AMD) and Intel (INTC) are fighting for their share of the AI PC market. The edge silicon war is just beginning, and the winners here get paid on every device that ships. 

Key names: QCOM, ARM, NVDA, AMD, INTC

2. Sensors and Machine Vision: Giving AI Eyes and Ears

Image sensors, depth cameras, radar, lidar, microphones – these are the eyes and ears of every robot, wearable, and autonomous vehicle. 

Apple (AAPL) is reportedly exploring camera-equipped AirPods. Though the timeline remains fluid, the larger direction is clear: wearables are gaining the ability to see and interpret the world around us. That creates a new demand cycle for smaller cameras, microphones, depth sensors, and related components.

Key names: Ambarella (AMBA), ON Semiconductor (ON), STMicroelectronics (STM), Sony (SONY), Cognex (CGNX)

3. Advanced Optics: The Interface for AI Glasses

AR glasses and AI eyewear aren’t a consumer curiosity anymore – they’re a hardware category. And the bottleneck? Optics. 

Waveguides, photonic displays, specialty glass, and laser projection systems are what separate a pair of glasses from a heads-up display. Corning (GLW) and Coherent (COHR) are two of the most underappreciated Physical AI plays in the market for precisely this reason. Applied Materials’ pivot into intelligent optics manufacturing signals how seriously the semiconductor equipment industry is taking this category. 

Key names: AMAT, GLW, Lumentum (LITE), COHR

4. Robotics and Automation: Where Physical AI Does the Work

Unitree proved investors are ready to pay for the humanoid-robot story. The next wave will belong to robots that can earn their keep.

Genesis AI’s Eno is built to adjust to changing tasks and environments. Traditional automation follows a script. Eno is designed to respond when the real world refuses to follow it. 

Companies like Symbotic (SYM), Teradyne (TER), Rockwell Automation (ROK), and Honeywell (HON) are already deploying AI-driven automation in factories and warehouses at scale. Tesla‘s (TSLA) Optimus will keep drawing the headlines. Much of the near-term revenue, however, is already coming from less glamorous automation systems working inside factories and distribution centers. 

Key names: SYM, TER, ROK, HON, TSLA

5. Memory, Storage, and Power: Feeding Edge AI

On-device AI needs more memory and storage than ordinary electronics. A wearable, robot, or AI PC has to hold models locally, process large streams of sensor data, and deliver sudden bursts of computing power without draining the battery or overheating.

That supports demand for next-generation low-power memory, larger storage systems, power-management chips, and analog components that translate signals from the physical world.

Micron (MU) is already winning here with its LPCAMM modules for AI PCs. The storage plays – Seagate (STX), Western Digital (WDC), SanDisk (SNDK) – get a demand tailwind as every edge device needs local model storage. 

Key names: MU, STX, WDC, SNDK, Monolithic Power (MPWR), Analog Devices (ADI), Texas Instruments (TXN).

6. Connectivity: Keeping Physical AI Connected to the Cloud 

Even edge AI needs the cloud. Local inference handles the latency-sensitive tasks; cloud AI handles the heavy lifting – model updates, data sync, fleet coordination for robotaxis, telemetry from billions of wearables. 

That means the optical networking and connectivity layer is a direct beneficiary of Physical AI scaling. Robotaxis syncing to the cloud. AR glasses streaming map data. Industrial robots phoning home with diagnostic telemetry. Broadcom (AVGO), Marvell (MRVL), Arista (ANET), Ciena (CIEN), Credo (CRDO), and Corning are all toll roads on that data highway. 

Key names: AVGO, MRVL, ANET, CRDO, CIEN, GLW

How to Invest in Physical AI Stocks Without Chasing One Robot

Unitree’s debut will make the robot maker the obvious stock people want to chase.

The broader Physical AI opportunity is much larger than any one robot company.

Every humanoid, wearable, AI PC, smart-glasses platform, autonomous vehicle, and industrial machine pulls demand through the same hardware layers: chips, sensors, optics, memory, storage, power management, and connectivity.

The winning device may change. The need for supporting hardware does not.

That creates an enormous opportunity across public markets. It also highlights an increasingly difficult task.

As this boom stretches across edge-chip suppliers, optics companies, robotics specialists, memory manufacturers, power-management firms, and networking stocks, investors have to decide which names deserve capital, how much weight each one should carry, and where different holdings depend on the same underlying trend.

Louis Navellier, Eric Fry, and I have gone back through more than 200 AI recommendations and narrowed the field to roughly 20 stocks we believe deserve capital now, each with a recommended portfolio weight. 

Unitree’s debut shows how quickly an exciting AI theme can attract capital – and how easy it is to chase the company making the loudest headline.

See where Louis, Eric, and I are focusing our attention now.

The post The Most Important Part of Unitree’s IPO Wasn’t the Robot appeared first on InvestorPlace.

As I write on Wednesday, the bond market just got rescued…for the moment.

Yesterday, the 30-year Treasury yield touched 5.33% – a 19-year high. The “Bond Vigilantes” were in open revolt, and the question was how much higher they’d push before something in the stock market broke.

This morning, the Treasury blinked.

Secretary Scott Bessent’s department announced it will more than double the size of its debt buybacks – stepping in as a buyer of older, longer-dated bonds to relieve the long end of the yield curve that had seen what amounts to a buyers’ strike since late June.

The reaction was immediate. Yields tumbled, and stock futures jumped. As I write late morning, the 30-year has backed off to about 5.19%, and the 10-year sits at 4.65%.

So, crisis averted?

Not so much. This move is a band-aid on a much deeper wound – it does nothing about the thing that the Bond Vigilantes are furious about.

First, so we’re all on the same page, the term “Bond Vigilantes” was coined in the 1980s by economist Ed Yardeni – who, as it happens, is Louis Navellier’s favorite economist.

It describes bond investors who sell off Treasurys when they think Washington or the Fed is being reckless – runaway government spending, say, or a central bank that’s gone soft on inflation. By dumping bonds, these investors drive yields higher, effectively punishing policymakers with steeper borrowing costs.

In other words, they act like vigilantes – enforcing the financial discipline that politicians and central bankers won’t. And in recent weeks, they’ve been on the march.

The chart below shows the 30-year Treasury yield exploding from about 4.83% in late June to yesterday’s 5.33% peak – the run-up that finally forced the Treasury’s hand.

So, why are the vigilantes so mad?

Part of it is the same old story – debt.

Washington keeps spending far more than it takes in, and every new Treasury auction floods the market with more bonds buyers must absorb – more supply, higher yields. The government’s interest tab now tops $1 trillion a year, and it only grows as cheaper old debt rolls over into today’s higher rates.

But that slow-burn debt problem isn’t what lit the fuse this summer. The real kicker is the new man at the Federal Reserve – and what he hasn’t said.

When President Trump installed Kevin Warsh as Fed chair in May, Trump had one thing in mind: lower interest rates. But Warsh took over with inflation still running stubbornly above the Fed’s 2% target – by his own count, for 63 straight months – and he’s now held rates steady at the first two meetings he has chaired.

But what the bond vigilantes really don’t like is how Warsh has stripped away the Fed’s forward guidance – the carefully worded hints about where policy is headed.

Warsh’s theory is that markets should price the economy on their own, rather than simply take their cues from the Fed’s script. At his July post-FOMC press conference, Warsh leaned into the idea that the bond market was already doing the Fed’s tightening for it:

The economy – output is solid. Capex and productivity are strong – labor markets – solid, steady.

The bond market – the Treasury market – it seems to be saying that as well… that’s why we’re seeing a tightening both in nominals and in reals, even while, at some level, we haven’t done much in 42 days.

The markets have done quite a bit.

To a trader worried about 4-5% inflation, that lands as a Fed chair who’s comfortable letting the bond market do his job for him, while offering almost no plan of his own to crush inflation. Warsh even conceded there’s “no magic wand” to bring prices down.

The market’s verdict was swift. Stocks tumbled after Warsh’s comments – the Dow logged its worst day since April 2025 – and long-bond yields spiked, with the 30-year vaulting past 5.2% to its highest level since 2007.

Yardeni, who coined “Bond Vigilantes” in the first place, was blunt: talking tough while doing nothing only drains the Fed’s credibility – and if the Fed won’t police inflation, the vigilantes will.

So, does the Treasury’s rescue this morning actually fix anything?

No.

The Treasury isn’t retiring debt or shrinking the deficit. It’s buying back older, less-liquid long-dated bonds and funding those purchases by issuing other Treasurys – recycling paper off dealers’ balance sheets to grease a market that had gotten sticky at the long end. It’s basically just rearranging the maturity schedule.

In other words, the Treasury is treating a symptom, but not the underlying ailment. And that ailment is exactly what we just walked through. The vigilantes aren’t dumping 30-year bonds because dealers are short on shelf space. They’re dumping them because Washington is spending over $1 trillion a year just to service its debt, and because they don’t trust the new Fed chair to bring inflation back to 2%.

A liquidity operation, however well-timed, does nothing about either. The deficit is untouched. Warsh is untouched. Inflation is untouched.

So, while this morning bought the market some breathing room, it didn’t fix the core issues that the vigilantes care about.

Our tech expert Luke Lango saw this standoff coming

Back in May – the week Warsh was confirmed – our technology investing expert, Luke Lango, editor of Innovation Investor, laid out how this would play out. He argued the bond market was about to put the new chair to the test:

The bond market is looking at a Fed chair installed specifically to cut rates, staring at a macro backdrop where inflation could hit 5% by year-end, and saying: “Drop the rate cut act. Be an adult in the room.”

This is the bond vigilantes at work. And the only way to get them to stand down is for Warsh to prove he’s serious about fighting inflation.

Hawkish commentary alone might do it. An actual rate hike would absolutely do it. You bring up the short end to save the long end.

That last line is the counterintuitive heart of it. Luke’s point was that a rate hike – the very thing stock investors normally fear – could actually rescue this market.

Raise short-term rates, prove you’re serious about inflation, and you take away the vigilantes’ reason to keep dumping long bonds. The long end settles. And paradoxically, the pressure comes off the AI trade.

We’ll be listening for clues about rate policy from Warsh when he speaks at the Jackson Hole Symposium next week, but if history repeats, he’ll bend over backward to avoid saying anything that even hints at coming rate policy.

If/when yields return to climbing, at what level will they derail stocks?

This is the question that matters for your portfolio. Luke’s line in the sand is 5% on the 10-year Treasury.

Here he is with why, below that line, the AI bull market survives:

Most of the gains in this market aren’t being driven by multiple expansion. They’re being driven by earnings growth… The S&P 500’s forward three-year EPS CAGR sits at roughly 16%.

That math works — even with the 10-year at 4.5 to 5%. We’re talking a 5 to 10% pullback, then a resumption of the AI trade.

But break above 5%, and the story changes. Luke says that level is where Main Street breaks as the bruised consumer becomes a broken one. And a broken consumer would impact Big Tech’s revenues, leaving the hyperscalers with fewer dollars to fund their AI capex commitments, putting the whole trade in danger.

Back to Luke:

And that 16% forward EPS CAGR? It collapses to 8%, maybe 5%.

That’s the Achilles heel.

But even if/when the Bond Vigilantes return, keep in mind Louis’ take

Louis watched the hottest AI names sell off yesterday and basically shrugged.

The first reason behind his measured response is the calendar. It’s mid-August, Europe is on holiday, and the desks that are still staffed are thin – the kind of low-liquidity market where every scary headline gets amplified.

His second point reframes the story. Louis argues the recent yield spike isn’t a made-in-America, blame-Warsh event at all. It’s global.

From his Growth Investor Flash Alert podcast yesterday:

The bond vigilantes are forcing the yields to go higher on Britain, France, even Germany and Japan… and what all these societies have in common is they are losing households. So, there’s fewer people paying into the system.

His third point dovetails with Luke. Louis is adamant the AI boom is intact – and takes direct aim at the fear that the vigilantes will crush valuations:

The other narrative you’ll hear is that the bond vigilantes are going to demand lower P/E ratios. Well, P/E ratios are collapsing because the earnings are so strong.

We covered this reality in Monday’s Digest. Earnings are soaring today, taking pressure off valuations.

One last reason to be calm during this yield spike

Let’s go straight to the source – Yardeni himself.

Yesterday, CNBC ran a story highlighting that Yardeni isn’t “pushing the panic button,” but is watching more closely as the 10-year yield flirts with 5%. But even if it hits 5%, Yardeni doesn’t conclude that we’ll keep soaring from there:

I think at 5% we’ll have plenty of buyers, as we saw in 2023.

So, the man who coined “Bond Vigilantes” and our in-house tech expert have independently landed on the same number: 5% on the 10-year. Below it, buyable. Above it, a problem.

As I write, the 10-year sits around 4.65% – a nice pullback thanks to this morning’s news.

Coming full circle, the vigilantes got a band-aid this morning, but not a solution. The Treasury gave the market some breathing room, but the bond vigilantes’ primary gripes remain exactly where they were yesterday.

So, from here, watch two things: whether Warsh finally signals he’s serious about inflation (hawkish talk, or the rate hike Luke thinks would settle things), and whether the 10-year pierces 5%. North of that line, it’s time to start getting defensive. But leading up to it, “buy the dip” remains on the table.

So, which AI stocks would you buy on the dip? And how much?

Those are two of the questions our three experts – Louis, Luke, and Eric Fry of Fry’s Investment Report addressed this morning when they unveiled their rebuilt AI Revolution Portfolio. It’s a “from-the-ground-up” refresh of the elite AI stocks they believe are built to survive exactly this kind of macro test.

This morning’s presentation also brought a huge twist. After 47 years of being in the market, Louis announced a major change to his role.

If you missed it all, we’ve posted a free replay. To watch it now, just click here.

We’ll keep tracking the vigilantes – and that 5% line – in the days ahead.

Have a good evening,

Jeff Remsburg

The post Will Higher Bond Yields Break the AI Bull Market? appeared first on InvestorPlace.

AI is spreading into personal devices, consumer agents, custom chips, memory, networking, power, and software – creating more opportunities, but also making it harder to know which stocks belong together.

That’s why my InvestorPlace colleagues Louis Navellier, Luke Lango, and I just held a special presentation where we discussed:

• How AI is entering a “Super Exponential” phase, with its capabilities and revenues growing faster than ever.
• How this boom is creating an unusually wide gap between winners and losers.
• And how stock picking alone isn’t enough anymore.

Portfolio construction matters as much as – or more than – finding individual winners. Position size, diversification and how stocks interact with one another are becoming critical.

We want to thank all of you who joined our broadcast. If you missed it, you can catch a replay here.

Now, after the event, Luke is joining us to discuss why AI investing has evolved beyond simply owning Nvidia Corp. (NVDA) and the major hyperscalers. The key challenge for investors is no longer finding AI winners, but figuring out how to combine them into the right portfolio.

And Luke has the answer…

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.

Watch Louis, Eric, and me unveil the newly rebuilt AI Revolution Portfolio, right here.

We’ll discuss the stocks we see winning, the recommended allocations, and the thinking behind our positions.

Click here for all the information.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post AI Has More Winners Than Ever – Here’s the Catch appeared first on InvestorPlace.

When Andrew asked it to add back the person it kicked from the waitlist, it replied: “Bad news — I can’t add them back”:

Australia’s cyber authorities are calling it the first known autonomous cyber attack in the country, prompted by a lone man who simply wanted to do some burpees.

It sounds pretty scary if you believe we’re all headed toward a Terminator-style “Skynet.” But the scary headlines miss the value here… this wasn’t a malfunction so much as it was a performance enhancement.

My read here is similar to when Anthropic abruptly disabled its newest frontier models, Claude Fable 5 and Mythos 5, after the U.S. government ordered it to suspend foreign-national access.

This couldn’t be more bullish.

In just minutes, Andrew’s Openclaw agent entered a system it’s never been in, inferred how the software worked, found an actual bug, and tested it in real-time. Importantly, it also was honest about its actions, and Andrew then had his agent draft an email disclosure to the gym’s software vendor.

In other words, AI is proving it can be a fairly competent junior security researcher for the price of an API call.

In fact, the length of task that an AI agent can complete singlehandedly has doubled roughly every seven months. Back in 2020, it could reliably handle about four seconds of human work. Today, it’s closer to 12 hours.

Each of those 12 hours of autonomous, agentic work is work companies can buy rather than hire, and each provides an attack surface companies must then defend. It’s both scary and bullish at the same time.

And there’s one chart that shows just how explosive AI is about to become…

The Most Bullish Chart I’ve Ever Seen

This chart shows that the median monthly AI spend per employee each month among the top 1% of AI-adopting firms is $7,400. While the median for all AI-adopting firms is just $12.

That gap is the entire growth opportunity.

If Company A spends $7,400 per employee per month and Company B spends $12, Company A produces more, faster, cheaper. Company B either matches it or loses its business.

That means adoption continues to grow exponentially until every firm is a big AI spender, the same way every firm is a big cloud spender.

This is extremely bullish for NVIDIA Corp. (NVDA), Advanced Micro Devices Inc. (AMD), Broadcom Inc. (AVGO), and more.

As demand climbs, compute stays undersupplied, and the supercycle has real longevity.

Today at 10 a.m. ET

But there’s just one problem… there are now more good AI opportunities than any person can follow.

Between Louis Navellier, Eric Fry, and me, we’ve issued more than 200 recommendations in the past year.

My Lumentum (LITE) position is up 645%, and Louis’ Nvidia call is up 375%.

Owning AI stocks is only half the job… how much you own and what you own are the deciding factors. So the three of us did something we’ve never done before. And after 47 years, Louis is announcing a major change to his role.

It goes live today at 10 a.m. ET, and you don’t want to miss it!

Reserve your spot here.

The post AI Spending Just Revealed a $7,000 Gap Between Winners and Losers appeared first on InvestorPlace.

As demand for computing power surges and new data centers become harder to build, he explains why some of the biggest opportunities may come from the companies supplying the infrastructure AI needs to keep growing.

That thinking helped shape our newly rebuilt AI Revolution Portfolio. Together, Eric, Luke and I narrowed more than 200 recommendations down to roughly 20 stocks we believe stand out today.

Tomorrow at 10 a.m. Eastern, we’ll reveal how we’re positioning for the next phase of the AI boom. Click here to reserve your spot now.

But first, here’s Eric with a look at where the next wave of AI opportunities could come from…

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

Hello, Reader.

In the 1989 film Field of Dreams, the famous line goes: “If you build it, they will come.” But in the AI boom, the saying may need an update:

“If you build it, communities will protest. But if you have already built it, they may come.”

The “it” here is data centers. As AI firms race to build more data centers, communities are increasingly pushing back against new projects.

On July 18 alone, 142 protests took place across 42 states in the first nationwide protest effort against the rapid expansion of AI data centers. And Data Center Watch reports that at least 75 U.S. data-center projects worth about $130 billion were blocked or delayed in the first quarter of this year.

At the same time, AI’s appetite for computing power continues to grow. That brings us to the “they” – AI companies desperate for more computing power.

A simple supply-and-demand problem is happening here: New capacity is becoming harder to build just as demand for AI computing continues to soar.

And that imbalance is creating a new opportunity.

When new capacity becomes harder to build, existing capacity becomes more valuable. And companies that already have the land, power and facilities needed for AI data centers could be sitting on valuable real estate – literally.

And a deal made this week between AI giant Anthropic and an unlikely infrastructure provider offers a glimpse of what that opportunity could look like.

So today, I’ll take a closer look at that deal to show you how one AI bottleneck can create opportunities across multiple industries. Then, I’ll reveal how we’re positioning for those very opportunities.

AI Buys What’s Already Built

Last week, Anthropic reportedly signed a 20-year, $9.1 billion deal with Riot Platforms, Inc. (RIOT) for 191 megawatts of data-center capacity at Riot’s Rockdale, Texas, campus. Riot expects the deal to generate about $9.1 billion through 2048, with an option that could push the total value to $16.1 billion. The capacity is expected to be delivered in phases, beginning in 2026 and continuing through 2028.

The key here is that Riot doesn’t have to start from scratch. The company, best known as a bitcoin miner, already has the land, power and infrastructure needed to support a data center. So, instead of using all of that capacity for bitcoin mining, it can lease it to AI companies, like Anthropic.

Riot already struck a deal with Advanced Micro Devices Inc. (AMD) for up to 200 MW of data-center capacity earlier this year. The Anthropic deal takes that strategy much further.

As demand for computing power rises and new data centers become harder to build, sites that already have power and infrastructure could become increasingly valuable, even if they were originally built for something completely different.

Anthropic and Riot’s billion-dollar deal shows how much AI companies are willing to pay for capacity they can actually access. But the bottleneck doesn’t stop at data centers. Building all this AI infrastructure requires a massive amount of power, equipment, and raw materials.

It reaches all the way down to the materials and equipment needed to build them.

That means AI’s rapid growth is creating investment opportunities at every rung of the AI ladder…

The Ladder of Opportunity

One single stock, industry, or sector simply can’t capture the entire opportunity. For instance, the technology needs:

Power generation – AI data centers need enormous amounts of electricity, and power producers supply it. As AI drives demand for new data-center capacity, companies that generate and sell that electricity can benefit.

Grid infrastructure – Data centers also need to connect to the power grid. Companies supplying transformers, substations, transmission equipment and other grid infrastructure are helping make the AI buildout possible.

Cooling – AI chips generate enormous amounts of heat, making cooling systems essential to keeping data centers operational. Companies providing liquid cooling, HVAC, and other thermal-management systems are well-positioned to benefit from the expansion of AI infrastructure.

Construction – Someone has to build all those data centers and power facilities. Construction and engineering companies that design and construct the infrastructure are another part of the opportunity.

Semiconductors – Companies like Nvidia Corp. (NVDA) supply the chips that provide the computing power AI systems require, making semiconductors a core part of the physical infrastructure behind the AI boom.

Memory – AI systems also require enormous amounts of DRAM, HBM, and other memory. So, memory manufacturers are supplying another critical component of the computing infrastructure needed to scale AI.

In all, the AI Revolution has created an enormous number of potential investment opportunities. But the more this technology spreads, the harder it becomes to know which companies deserve your attention – and, just as importantly, which don’t.

Separate the Best From the Rest

There are now so many ways to invest in AI that simply finding an AI stock isn’t enough. The challenge is separating the best opportunities from the rest.

That’s why my InvestorPlace colleagues Louis Navellier, Luke Lango and I have gone back through our AI research and narrowed our recommendations into a newly rebuilt portfolio, the AI Revolution Portfolio.

We first launched this portfolio back in 2023 to narrow the huge universe of AI-related companies down to what we considered the best-in-class opportunities. By combining our different investing strengths, we designed a portfolio that captures multiple parts of the AI ecosystem, rather than betting everything on one company.

And we’ve rebalanced it at pivotal moments in the AI Revolution. For instance, in 2024, AI developers were reaching the limits of brute-force improvements, creating a divide between companies that could adapt and those that couldn’t. So, in December of that year, we rebalanced our AI Revolution Portfolio to make sure we were positioned on the right side of that divide.

Since that rebalance in December 2024, our portfolio has risen 58% – more than double the Nasdaq Composite’s 25% return and nearly triple the Dow Jones Industrial Average’s 19% gain.

Now, we’re at another pivotal moment, where a single AI bottleneck could create opportunities across multiple industries.

We’ll be hosting a special event tomorrow, August 19, at 10 a.m. Eastern to unveil our new portfolio and show you exactly how we are positioning for AI’s next phase. Click here to reserve your spot now.

In other words, we’ve rebuilt it. Now, all that’s left is for you to come.

Simply click here to join us. We look forward to seeing you there.

Regards,

Eric Fry

Editor, Smart Money

The post AI’s Biggest Problem Right Now – And the Portfolio of Companies Solving It appeared first on InvestorPlace.

The public really hates data centers – but that could make you a lot of money.

Last month, I introduced an analytical framework I called “The Messy Middle” – the idea that AI won’t force us to choose between good and bad outcomes, but between two legitimate “goods” vying for priority. We won’t be able to have both in equal measure at the same time.

One example we profiled came from New York, where Gov. Kathy Hochul became the first governor to sign a law pausing the construction of new hyperscale AI data centers.

She gave up the “goods” of longer-term productivity gains, jobs, and the bigger tax base that those data centers would have delivered…in exchange for the “goods” of holding down electricity prices, protecting natural resources from potential pollution, and shielding communities from disruption.

Not right or wrong – simply a prioritization.

Now, this anti-data-center backlash isn’t limited to New York. It’s gathering momentum across the country at the very moment AI usage at home and at the office is accelerating, driving enormous demand for the very same data centers those communities are fighting.

That’s the Messy Middle setting up on a national scale. And while it could create real social tensions, it could also be incredibly lucrative for investors who know where to look.

Here’s our global macro investment expert, Eric Fry, to explain:

When new capacity becomes harder to build, existing capacity becomes more valuable.

And companies that already have the land, power and facilities needed for AI data centers could be sitting on valuable real estate – literally.

One company cashing in on the Messy Middle of AI’s infrastructure needs

Last week, Anthropic reportedly signed a 20-year, $9.1 billion deal with Riot Platforms, Inc. (RIOT) for 191 megawatts of data-center capacity at Riot’s Rockdale, Texas, campus.

Riot expects the deal to generate about $9.1 billion through 2048, with an option that could push the total value to $16.1 billion. The capacity is expected to be delivered in phases, beginning in 2026 and continuing through 2028.

Back to Eric:

The key here is that Riot doesn’t have to start from scratch.

The company, best known as a bitcoin miner, already has the land, power and infrastructure needed to support a data center.

So, instead of using all of that capacity for bitcoin mining, it can lease it to AI companies, like Anthropic.

As politicians and voters battle over the Messy Middle, companies like Riot that bypass these political and administrative bottlenecks stand to benefit.

Beyond RIOT, check out Core Scientific (CORZ). It holds massive, pre-existing gigawatt-scale power infrastructure and has been a pioneer in signing long-term, high-performance computing contracts with hyperscalers.

There’s also CleanSpark (CLSK), which commands a broad pipeline of powered industrial sites with approved grid connections. These sites can be retrofitted for AI data workloads or alternative compute.

The thread connecting all three stocks is the same: each one already owns something that’s suddenly become scarce – power, land, and grid access that would take years and a bruising permitting fight to assemble from scratch today.

But these infrastructure landlords are only the first rung on the AI opportunity ladder. There are plenty more rungs.

Think about everything it takes to turn a powered site into a working AI data center

You need the electricity itself, which points to power generators… You need to move that electricity, which points to transformers, substations, and transmission gear… You need to keep the chips from cooking themselves, which points to industrial-scale cooling… You need firms to design and build the facilities… And, of course, there’s everything that goes inside – the semiconductors and memory that do the actual computing.

Every one of those rungs is its own bottleneck. And every bottleneck is its own opportunity.

That’s a lot of ground for any single investor to cover, which is exactly why Eric, alongside Louis Navellier of Growth Investor and Luke Lango of Innovation Investor, have spent recent weeks covering it for you.

The three of them have rebuilt their collective AI Revolution Portfolio from the ground up – designing it to capture multiple rungs of that ladder rather than bet everything on a single stock or sector.

Our three experts first assembled this portfolio of elite AI stocks in 2023, then rebalanced it at the end of 2024 as the AI race shifted. And they see this moment – where a single infrastructure bottleneck is spilling opportunity across a dozen industries – as the next pivot point.

They’re pulling back the curtain tomorrow morning at 10:00 a.m. Eastern, when they’ll unveil their rebuilt portfolio and walk through exactly how they’re positioning for AI’s next phase.

Back to Eric:

The AI Revolution has created an enormous number of potential investment opportunities. But the more this technology spreads, the harder it becomes to know which companies deserve your attention – and, just as importantly, which don’t.

That’s what tomorrow is about – separating the best opportunities from the rest.

To join Eric, Louis, and Luke, just click here to register. We’ll see you tomorrow at 10:00 a.m. Eastern.

“But hold on, Jeff, if we see a wave of data center moratoriums across the nation, won’t that kill the AI trade?”

It’s tempting to see the backlash as pure upside: choke off new construction, and whoever already owns power gets richer. That’s the bull case, and I think it’s largely right. But a sharp reader should be asking the harder question – if the backlash keeps spreading, doesn’t it threaten the entire AI infrastructure trade?

Take an AI picks-and-shovels supplier like Vertiv Holdings Co. (VRT). Its order book has swelled past $12 billion on the power and cooling gear these facilities need. But those orders only convert to revenue if the data centers actually get built and powered. Slam the brakes, and a backlog is just a promise.

So, a widespread national moratorium on data centers isn’t something to brush off idly. Let’s walk through it.

Beyond memory, one of the most significant constraints on AI today is power. There simply isn’t enough of it, fast enough, to feed every planned facility.

When politicians layer permitting delays, grid audits, and ratepayer fights on top of an already power-starved buildout, they genuinely slow the pace at which that backlog turns to cash.

So yes, slower-than-expected revenue would ding AI infrastructure companies that have told Wall Street those revenues are coming. But a ding isn’t the same as a broad AI crash.

Here’s the part the doomsayers skip

Earlier this month, headlines trumpeted that even data-center leader Texas was slamming the brakes on its data-center rollout. It was positioned as a harbinger of doom for AI.

Yes and no.

Texas Gov. Greg Abbott ordered regulators to audit data centers waiting to plug into the state grid and deny those that didn’t measure up.

It was a screen, not a stop – and it came with a giant loophole: facilities that build their own on-site power can skip the grid queue entirely. Even his critics shrugged, with one Texas official calling it “all hat and no cattle” – Texas jargon for all talk and no action.

Sound familiar? On-site power is precisely what Riot, Core Scientific, and CleanSpark already have.

Meanwhile, all year, as the moratoriums piled up, the spending went up. The four biggest hyperscalers now plan roughly $725 billion in capital expenditures this year – the money they pour into building all this – up about 77% from 2025.

But how has this been happening even as the moratoriums have been growing? Because as we noted in our Messy Middle Digest last month, resistance in one state doesn’t kill AI demand – it relocates it.

A project blocked in New York or stalled in Texas moves to a friendlier corridor, another state, or offshore. The chips still get bought.

So, the backlash doesn’t break the trade, but it does redistribute the winners – and raises the cost of being on the wrong side.

Returning to our question then…

How worried should you be about your AI infrastructure stocks considering this growing data center backlash?

I’d call it a yellow flag, not a red one – but with one genuine red tail.

The yellow flag is timing. Delays and cost overruns can bruise these richly priced stocks even when demand remains intact.

Returning to Vertiv, we just watched it happen here in Q2. The company reported record demand and raised its full-year guidance, yet the stock still dropped about 12% as revenue slipped due to project timing and supply-chain snags. Nothing was wrong with the demand – only the pace of delivery – and the stock got slammed anyway.

The red tail is the one we flagged back in July: isolated state pushback just routes capital elsewhere, but a coordinated wall – a federal pause, or so many states acting at once that there’s nowhere friendly left to go – could truly break the trade. Today, that’s a risk to watch, but not the base case.

One thing to watch above all: the day that hyperscaler spending guidance stops rising. That’s the signal to take seriously. Until then, rising guidance is your green light to stay in the AI infrastructure trade.

Which is why the move today isn’t “sell,” it’s “sort”

This is the Messy Middle turned on your own portfolio. For every AI holding you own, ask a single critical question…

Which side of the productivity-versus-disruption tradeoff is it on?

The scarcity beneficiaries – the power, grid, cooling, and existing-capacity names – get more valuable as building gets harder. The chipmakers are largely insulated, because demand just relocates. The vulnerable ones are the opposite: names pinned to a single contested region, or priced as if the buildout will be cheap, fast, and unopposed.

All this brings us back to tomorrow’s AI Revolution Portfolio refresh, with updated positions spread deliberately across all the rungs of the AI ladder rather than concentrated on any one of them. Here’s that link again to reserve your spot.

We’ll keep tracking the backlash – and both sides of the trade it’s creating – in the months ahead.

Have a good evening,

Jeff Remsburg

 (Disclosure: I own VRT.)

The post Don’t Sell Your AI Stocks – Sort Them appeared first on InvestorPlace.

Ehrlich chose chromium, copper, nickel, tin, and tungsten. Two hundred dollars of each cost $1,000 total, priced in 1980. If that basket was valued more over a decade later, Simon would pay the difference. If it cost less, Ehrlich would be on the hook.

The world added more than 800 million people over those 10 years. Every one of those five metals cheapened in value (after adjusting for inflation). Ehrlich wrote the check.

I keep thinking about that check, because Wall Street channeled its inner Ehrlich on bet concerning artificial intelligence stocks.

In a nutshell, critics rebranded the “scarcity” story as a “peak spending” story. The claim was that hyperscaler capital budgets had topped out, so everyone who bought into the buildout was about to watch as it dried up. That narrative blew up a lot of AI stocks. It took 30%, 40%, and 50% out of some of the strongest businesses in the AI infrastructure complex.

Then earnings season arrived with a bang.

The peak spending thesis is complete hogwash, and the past two weeks prove it emphatically.

So let me walk you through what these companies reported, what the July inflation print does to the rate picture, and why the buy window that just opened does not extend to the rest of the market. You can watch me discuss this in full in the latest episode of Being Exponential With Luke Lango below:

The Neoclouds Settled the Argument

Hyperscalers tell you how much they plan to spend. Chip vendors tell you what is shipping. The Neoclouds tell you something better: whether customers actually rent that infrastructure, what price they pay for it, and how long they commit to it. Utilization, pricing, and forward commitments. That is the read on real demand, and we just heard from the two biggest players in the group.

CoreWeave Inc. (CRWV) grew revenue about 112% year-over-year to $2.6 billion, with adjusted EBITDA of $1.5 billion at a 59% margin. Management guided to an annualized run rate of $18.5 billion to $19.5 billion by year-end. The company finished the second quarter with a $104 billion backlog, up 246%.

Nebius Group N.V. (NBIS) grew faster, which is one reason I recommend it as my favorite name in the space. Revenue jumped 454% to $582 million. Annualized run-rate revenue climbed 56% sequentially to $3 billion. Adjusted EBITDA reached $236 million at a 41% margin. Committed backlog sits above $40 billion, and management said it could sell out all of its planned 2027 capacity today.

Triple-digit revenue growth with 40%-plus margins. You could not dream up better numbers.

Here is the line that matters most. Both companies said newly deployed capacity sells out the moment it comes online. Physical supply is the binding constraint on growth right now. Demand sits there waiting for racks to get plugged in.

That was a rough week to be short Nebius.

Optics Delivered the Knockout

Then we heard from Lumentum Holdings Inc. (LITE), one of my favorite optics names and one of my favorite AI infrastructure names, clean and plain.

Fourth-quarter revenue grew 109% year-over-year. And the first-quarter guide calls for roughly 130% growth.

Sit with that, because it is the most important data point of the past two weeks. A company doing triple-digit revenue growth is guiding for faster triple-digit revenue growth. In a peak spending world, a high-octane supplier like Lumentum decelerates quarter over quarter. Instead, the growth rate accelerates. The pie is getting bigger, and the rate at which it gets bigger is going up too.

The structural story is simple. Every new GPU generation produces more data, runs at faster lane speeds, and demands more bandwidth at lower latency, so AI creates a permanent increase in optical content per system – 800G today, 1.6T and 200G per lane through 2027, then co-packaged optics around 2027 to 2028.

Lumentum is clearly winning dollar share. That does not translate one-for-one to Applied Optoelectronics Inc. (AAOI), Coherent Corp. (COHR), or Fabrinet (FN), though it tells you the whole market is doing extremely well. Fabrinet has the weakest chart in the group, which may make it the most attractively positioned name in it.

Hon Hai, Astera Labs, Arista Networks, Lattice Semiconductor, TTM Technologies, SiTime, and GlobalFoundries all reported the same way. When a narrative runs headfirst into a wall of data that rejects it this emphatically, the narrative loses.

Sentiment and Fundamentals Have to Reattach

In July, sentiment and fundamentals detached. Chicken Little took over the tape while the underlying businesses kept compounding.

Detachments like that resolve one of two ways. Either fundamentals weaken to meet the narrative, or the narrative strengthens to meet the fundamentals. Two weeks of earnings just told us fundamentals are strengthening, so sentiment has to come up. Both the SMH and the SOXX put in V-shaped recoveries off their 100-day moving averages with oversold RSI readings and bullish MACD crossovers. Technical confirmation now sits alongside earnings confirmation.

The macro cooperated too. July CPI came in soft enough to weaken the case for another Fed hike without signaling that the economy is falling apart. Core inflation slowed to 2.5%, its lowest reading in roughly five years, and core CPI is running at 1.6% annualized over the past three months. That real-time trend sits below target while the economy shed about 20,000 jobs in July. Nobody hikes into that. Take the hike off the table, and lower long-term yields feed straight into long-duration assets like AI stocks.

The read for consumer stocks is uglier. Wage growth of 3.2% against 3.4% headline inflation leaves real wages negative again, and that weakness shows up in prints like Dutch Bros and Sweetgreen. The bifurcation that has defined this market since ChatGPT launched persists.

So the buy window is open. And the buy window is open for AI.

Which AI, Though?

That question is where good investors go wrong.

Between Louis Navellier, Eric Fry, and me, InvestorPlace published more than 200 recommendations in the past year, the vast majority connected to AI in some way. You could be right about every theme in this article and still end up with a refrigerator full of ingredients and no meal. Owning the right AI companies is half the job. How much you own of each one, and what you own alongside it, decides your outcome.

So Louis, Eric, and I went through our entire universe of AI research and hand-picked the best ideas in it. Plus, Louis is announcing something Wednesday that he has never done in 47 years in this business.

I cannot go further today. What I can do is make sure you hear it first.

Add your name to the AI Revolution signup list right here. Once you’re on the list, you’ll get the announcement the moment it goes live Wednesday, no need to do anything further except listen to what we have in store for you.

And for the full breakdown of these earnings, the charts, and the macro picture, watch this week’s episode of Being Exponential.

The post The AI Stock ‘Peak Spending’ Panic Just Lost Its ‘Ehrlich Bet’ appeared first on InvestorPlace.

Bears have a math problem.

Perhaps the biggest gripe against this bull market has been overvaluation – stock prices bid up to unsustainable levels by greedy investors who care little for fundamentals.

Sure, some stocks have outrun their fundamentals. But that case gets hard to make across the board once you factor in forward earnings.

In fact, the opposite is happening. Even as stock prices have been climbing, valuations have been falling thanks to one powerful reason.

Earnings are climbing even faster.

Here’s the math the bears keep missing. A valuation multiple is just a fraction – price divided by earnings. The bears fixate on the numerator, rising prices, while ignoring what’s happening beneath it…

The denominator – corporate earnings – is growing even faster. And when the bottom of a fraction grows faster than the top, the fraction itself shrinks. That’s how valuations can fall even as prices climb.

Better yet, that earnings engine appears poised to keep running.

Legendary investor Louis Navellier highlighted this in last Friday’s issue of Breakthrough Stocks. After detailing the phenomenal Q2 earnings season we’re wrapping up, he shifted his gaze forward, noting:

Companies across all 11 S&P 500 sectors have increased their outlooks for the second half of 2026.

Bespoke reports that of the companies that have already announced results, more than 15% have increased guidance. Historically, over the past decade, 10% of companies have raised their guidance.

Why is this important? The phenomenal earnings environment will persist through year-end (and likely well into 2027, too).

Keep that “well into 2027” line in mind – it becomes important in a moment.

Now, let’s see what all that earnings power has done to valuations. Let’s go to our hypergrowth expert, Luke Lango, editor of Innovation Investor.

From last Friday’s Daily Notes:

FY26 and FY27 EPS estimates are both up roughly 16% since the start of the year, while the index is up about 14%.

At the same time, the S&P 500’s forward P/E has actually fallen from roughly 23.2x to 21.5x. 

Luke then makes the key point that strikes at the bear case…

Investors aren’t just paying more for the same earnings stream – basically, the FOMO-driven bidding of a late-stage bull. Instead, the earnings stream itself is getting bigger.

Here’s Luke with the takeaway:

That is the opposite of a speculative, sentiment-driven rally.

In fact, earnings are so strong that Luke makes the case for another 25% of upside in the S&P – without the sentiment multiple budging at all. Returning to Louis’ call that the robust earnings environment will persist well into 2027, Luke’s upside math rests on exactly that:

If the trend continues through year-end, 2027 EPS near $440 at a 22x average multiple – around the market’s average since early 2024 – implies a ~9,680 S&P 500 target, roughly 25% upside from here.

Of course, if the market rises double digits from here, investor sentiment won’t remain static. Higher prices will attract more buyers, likely resulting in a higher sentiment multiple alongside climbing earnings. Put it altogether and Luke’s case for 25% upside could easily become 30%+.

Now, if this plays out, it’s likely to exacerbate a good problem that Luke and Louis have been dealing with recently. And if you’re an AI Revolution Portfolio subscriber, you have it too…

As AI surges, don’t forget the blocking and tackling of portfolio construction

Last August, Luke and Louis, alongside our global macro specialist Eric Fry, came together to create the AI Revolution Portfolio. This is a single portfolio holding our three experts’ highest-conviction AI ideas.

The optical-networking company Lumentum (LITE) was one of their picks. Its lasers and optical components help move data through AI infrastructure using light. As the buildout scales, that technology becomes more essential.

Since our experts put it in front of their readers last year, LITE has surged 680%. And that’s where subscribers run into a nice problem.

Here’s Luke:

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…

One earnings report, customer delay, supply-chain problem, or change in AI infrastructure spending can now have an outsized impact.

So, what’s the action step if you find yourself in this position?

If you followed Luke, Louis and Eric into the AI Revolution Portfolio and own LITE – or you own any other high-flier that now commands a lopsided weighting – consider rebalancing. That means selling part of your winners to add to your laggards.

Selling a stock that’s working this well feels counterintuitive. But it’s the only mathematical way to guarantee you buy low and sell high.

By rebalancing, you achieve two critical goals: one, you turn “paper wealth” into real, permanent gains; and two, you bring your portfolio back to a risk level where you can sleep peacefully at night by addressing concentration risk.

But Jeff, what about the idea that investors underperform by selling their winners too early and holding their losers too long?

A great objection.

Countless investors destroy their long-term returns by selling great companies at the first sign of a drawdown after a strong move higher (missing even greater gains to come), while stubbornly holding their dogs all the way to the bottom (waiting for the rebound that never comes). Those are mistakes that are important to avoid.

But there’s a massive difference between panic-selling a winner after, say, a 55% run, and systematically managing your risk after nearly 7Xing your money.

Plus, when a stock like LITE skyrockets from 5% to 29% of your portfolio, rebalancing isn’t foolish – it’s recognizing that the math of your risk has fundamentally changed.

You now have nearly a third of your portfolio riding on one stock. Was that in your original plan? If not, don’t let it become your current plan by default.

Back to Luke:

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.

If you decide that rebalancing is the right call, the action step is simple – trim your position back to your original target, or to whatever size fits your current thesis and lets you sleep at night.

Meanwhile, keep your eyes open for the next potential 680% winner now that you have a wad of fresh capital

As I write, the AI Revolution Portfolio stock posts an average gain of 108%. Of course, this reflects outperformance that has already happened – the question is, where will such outperformance happen next?

Well, Luke, Louis, and Eric have ideas.

Back to Luke:

After combing through more than 200 AI recommendations, Louis, Eric, and I narrowed the field to roughly 19 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.

This Wednesday at 10:00 a.m. Eastern, our experts will reveal this “rebuilt” AI Revolution Portfolio. It contains the next wave of potential AI winners handpicked by our experts. But importantly, it’s a deliberately built, complementary portfolio – not a random pile of AI stocks.

As Luke notes:

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.

To see it when it goes live, as well as where our experts believe the AI Revolution goes next and how to position your portfolios for it, just click here to reserve your seat for Wednesday’s event at 10:00 a.m. Eastern. 

In the meantime, if you own LITE, congratulations.

Shifting gears, what will the Fed make of glum consumer sentiment and pessimistic inflation expectations?

Last Friday, the University of Michigan’s monthly Consumer Sentiment index reading dropped to 51, from 55.2 in July.

This is above the lows in the mid-40s seen earlier this year, but it still reveals considerable pessimism about the economy – mostly about prices.

Let’s return to Luke’s Daily notes for more color on the inflation angle relative to income:

Just 8% of consumers now expect their income to outpace inflation over the next year, down from 18% in December 2024.

That matches the deterioration in real purchasing power, with real average hourly earnings down 0.2% year over year in July. 

To what extent have these inflation expectations and waning hourly earnings been affecting the Fed?

We could get clues this Wednesday. That’s when we get the minutes from the Federal Reserve’s July FOMC meeting. It will be interesting to read how this “family fight,” as Fed Chair Kevin Warsh calls it, will play out.

Three regional Fed presidents – Beth Hammack, Neel Kashkari, and Lorie Logan – have been increasingly vocal about raising interest rates. The minutes should reveal more of their thinking – and how much weight they’re giving consumer sentiment and the Beige Book (a master summary of qualitative, anecdotal information from business leaders across all 12 Fed districts).

But even if this conversation gets greater airtime, Louis believes that September will come and go without a hike for one reason – the hard data.

Let’s jump to his Growth Investor Flash Alert last Friday:

We just had a negative payroll report and downward revisions. We just had very good inflation news. And, of course, now we got declining retail sales.

So, the Fed will not be raising rates in September.

To Louis’ point, the Fed tracks soft data like the sentiment survey, but it prioritizes hard data – actual economic activity over how consumers feel. And for nine of the 12 voting FOMC members, the hard data have not been making an overwhelming case for rate hikes.

Back to Louis for his bottom line:

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

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

We’ll circle back if the Fed’s minutes on Wednesday shed any new light on this.

Wrapping up

Put it all together, and the bull case is straightforward: earnings are doing the heavy lifting, valuations are actually compressing, and the Fed looks unlikely to stand in the way (at least in September).

That’s a rare combination – and it makes now a smart moment to get your own portfolio in shape, trimming your monster winners and lining up the next wave of AI outperformers.

Do that, and the only ones with a math problem will be the bears.

Have a good evening,

Jeff Remsburg

(Disclosure: I own LITE)

The post The 680% Winner You Should Trim Today appeared first on InvestorPlace.

That would normally be enough to make investors nervous. And there are a few reasons to wonder whether this rally is getting stretched.

For example, the Atlanta Fed recently cut its third-quarter GDP estimate from 5.8% to 4.3%, largely in response to softer July retail sales.

But much of that weakness reflected spending pulled forward into June by Amazon Prime Day, while other consumer categories remained healthy. So, I don’t view the downgrade as a major warning sign.

The more important question is whether the market itself is getting overbought.

On the one hand, stocks staged a furious rally over the past couple of weeks. On the other hand, S&P 500 earnings will likely be up by 50% by the time it’s all said and done. And when earnings are growing faster than stock prices, that means valuations are shrinking.

To answer this question, my daughter Crystal and I brought on the “Fibonacci Princess” Tammy Marshall in the latest episode of Navellier Market Buzz.

We unpacked what’s really behind the GDP downgrade, examined her technical analysis of the current market and she also walked us through the charts on some of the market’s biggest names.

She even reveals two stocks she’s bullish on right now.

Click the image below to watch the latest episode of Navellier Market Buzz.

If you haven’t already, don’t forget to click here to subscribe to my YouTube channel. And to learn more about Tammy, check out her YouTube channel here.

Plus, the grades in Stock Grader (subscription required) have been updated this week! Click here to plug in your own stocks and see how they’re rated.

Picking the Winners Is Only Half the Battle

The fact that there are still opportunities in this market doesn’t mean you should simply throw money at every stock that’s moving higher.

And we’ve already seen what can happen when an investor gets the big picture right but gets the portfolio wrong.

Consider what happened with Leopold Aschenbrenner. As I wrote about in a previous Market 360 article, at one point, his Situational Awareness hedge fund reportedly soared to $45 billion.

He was celebrated across the market, hailed as a “genius.”  Yet because he used too much leverage and had a concentrated portfolio in too few positions, he was forced to liquidate much of his portfolio when the market turned south.

Think about that.

He wasn’t wrong about AI. He was wrong about how he owned it.

I believe that’s one of the most important lessons investors can take from today’s market. Because going forward, it won’t be enough to simply identify the right AI stocks.

How much you own of each could matter just as much as which ones you own.

That’s a big reason why, after 47 years, I’m making a change to my role at InvestorPlace.

I’ll explain exactly what that means – and why I believe this change is necessary right now – during a special briefing this Wednesday, August 19, at 10 a.m. Eastern with my InvestorPlace colleagues Eric Fry and Luke Lango.

This is something we’ve never done before. And I believe it will allow me to do more to help you navigate the opportunities, and the risks, emerging from the AI boom.

Click here to reserve your spot for our special briefing.

Sincerely,

Louis Navellier

Editor, Market 360

The post Is This Record-High Market Overbought? (Plus: 2 Top Stocks to Buy Now) 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 Walmart Upgraded, Decker’s Outdoor Corporation Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

Nicky Hopkins, a classically trained pianist from Middlesex, England, was never a “front man” mauled by groupies. But the biggest bands of his era valued him for a particular expertise.

From the mid-1960s through the early 1980s, he was the most in-demand session pianist in rock and roll.

He was the guy the Rolling Stones, the Beatles, the Who, and Jefferson Airplane would track down whenever they needed someone to find, as the Rock and Roll Hall of Fame put it, “the magical spaces between the guitars that would wind up filling out the song.”

And yet, almost nobody outside the music industry knows his name.

The AI conversation in 2026 is focusing almost entirely on “front men” – sexy stories like data centers the size of Liechtenstein, autonomous robots, “endless” semiconductor demand, and the trillion-dollar roll of the dice that’s funding all of it.

Those conversations are certainly thrilling, but they are focusing narrowly on the “big names” of the AI Revolution. As a result, many investors are overlooking the companies that will find the “magical spaces” between existing technologies to create revolutionary industrial processes, commercial innovations, and scientific discoveries.

Biopharmaceutical companies are among that group.

The potential payoff for them is enormous. Drug discovery has always operated on brutal economics. Decades of work, billions of dollars, and a roughly 90% failure rate for compounds that reach clinical trials.

But AI could change all of that.

Fifteen months ago, Alex Zhavoronkov, the CEO of Insilico Medicine Cayman TopCo (ISLMF), sat for a Bloomberg Television interview and predicted that a drug conceived entirely by AI would reach pharmacy shelves by the end of the decade. “I would be surprised if we don’t see it over the next five to six years,” he said.

It was a bold claim, but not an entirely crazy one.

In June 2025, Nature Medicine published promising Phase II results for a new drug called Rentosertib, which treats a serious lung disease called idiopathic pulmonary fibrosis. Patients on the highest dose saw meaningful gains in lung function compared with a placebo group that continued to decline.

Artificial intelligence deserves most of the credit for this breakthrough. Insilico Medicine used its AI platform to figure out which biological target to attack in the body (a protein called TNIK) and then designed the drug’s chemical structure from scratch.

Other AI-assisted drugs had reached human trials before Rentosertib, but this marked the first time researchers published clinical data proving that AI could handle both jobs – finding the target and designing the drug – and see the result work in real patients.

Results like these are encouraging the pharma industry to dive headlong into new AI alliances that could supercharge drug discovery.

Eli Lilly & Co. (LLY) and Nvidia Corp. (NVDA) committed to a $1 billion, five-year AI drug-discovery collaboration in January 2026. The two companies are building a joint “co-innovation lab” in the San Francisco Bay Area, where Lilly’s biologists will work alongside Nvidia’s AI engineers to run experiments and train models on Nvidia’s BioNeMo platform.

AstraZeneca Plc. (AZN) entered a wide-ranging collaboration with the Chinese biotech CSPC Pharmaceuticals Group Ltd. (CSPCY) in mid-2025, worth more than $5.2 billion in potential milestone payments. CSPC’s AI platform will hunt for new drug candidates across multiple chronic disease categories, and AstraZeneca will handle development and commercialization, once candidates clear early trials.

Merck & Co. (MRK) committed $1 billion to a partnership with Google Cloud, layering that alongside existing collaborations with Tempus AI Inc. (TEM) (for precision-medicine biomarkers) and Mayo Clinic (for access to lab results, imaging, and clinical data that can validate AI models).

Nicky Hopkins never built an electric piano, but he breathed life into that instrument to create unforgettable songs. The best companies of the AI era will follow his example. They will use the instruments of this awe-inspiring new technology to “make music” with them.

Just as AI is helping transform biopharma, it’s creating opportunities across many industries.

I’ll share where to find the best AI opportunities below. But first, let’s take a look at what we covered here at Smart Money last week.

Smart Money Roundup

How My “Against-the-Grain” Approach Finds AI’s Hidden Winners

August 12, 2026

I’m putting my attention on the companies supplying the resources AI desperately needs. So, 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.

Don’t Get Distracted from the $22 Trillion AI Opportunity Ahead

August 13, 2026

Taking your eyes off the road can have serious consequences. The same is true for investing. While investors are busy reacting to the latest headline, AI is quietly reshaping one of the biggest forces “driving” the economy: work itself. 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.

AI’s $130 Billion Problem – and the Portfolio Created to Solve It

August 15, 2026

Companies that already have the land, power and facilities needed for AI data centers could be sitting on valuable real estate – literally. And a recent deal made between AI giant Anthropic and an unlikely infrastructure provider offers a glimpse of what that opportunity could look like.

I’ll take a closer look at that deal to show you how one AI bottleneck can create opportunities across multiple industries. Then, I’ll reveal how we’re positioning for those very opportunities.

Why The Fed’s Balancing Act Is Tilting in Wall Street’s Favor

August 16, 2026

My InvestorPlace colleague Louis Navellier has been watching two very important trends collide: cooling inflation and a weakening labor market. And that could put the Federal Reserve in a very interesting position.

Louis is joining us today to break down the latest inflation data, what it could mean for the Fed’s next move, and why he believes the setup may be increasingly favorable for stocks.

Let’s Make Music Together

The biggest AI opportunity may not belong to the companies building the technology. It may belong to the companies that know how to use it to create something extraordinary.

The problem is that once you start looking beyond the obvious AI names, the opportunity set gets enormous. There are now hundreds of companies using AI in different ways, across different industries – and figuring out which ones deserve your attention is becoming almost as important as finding the technology itself.

That’s where our approach to AI investing comes into play.

Rather than simply handing you another promising AI stock, my InvestorPlace colleagues Louis Navellier, Luke Lango, and I have gone back through our research and narrowed it down to the companies we believe belong together in one portfolio.

One instrument can make a sound, “magical” though it may be. But an orchestra, on the other hand, turns individual sounds into something greater.

Likewise, one AI stock might benefit enormously from the boom. But a portfolio of complementary companies can help investors capture that broader opportunity.

That’s the purpose of the newly rebuilt AI Revolution Portfolio.

Louis, Luke, and I have sifted through hundreds of ideas and created a portfolio of roughly 20 stocks, with specific allocation percentages for each position.

Join us on Wednesday, August 19, at 10 a.m. Eastern for a special presentation where we’ll unveil our new portfolio and show you exactly how we are positioning for AI’s next phase.

Click here to reserve your spot.

Regards,

Eric Fry

The post The Stocks Hiding in AI’s “Magical Spaces” appeared first on InvestorPlace.

For years, the bull case for space stocks has rested on a very simple idea.

Make it dramatically cheaper and easier to operate in orbit, and humans will find dramatically more things to do there.

Communications. Earth observation. Defense. Manufacturing. Pharmaceuticals. Artificial intelligence. Eventually, perhaps, enormous orbital data centers.

Earlier this year, the setup looked mostly like a convergence of future catalysts: a new White House space policy, a potential SpaceX (SPCX) IPO and a still-speculative orbital-compute narrative. That framing is now stale. Several of those catalysts have already happened – and the evidence behind the broader thesis is stronger than it was six months ago.

The better question today is not which space stock has the best quarter. It is whether the industry itself is entering a new regime.

I think it may be. And there are four catalysts that matter most.

Catalyst 1: Washington Is Moving From Space Policy to Space Execution

The policy catalyst is no longer just an executive order with a list of future deadlines.

On December 18, 2025, the White House issued the “Ensuring American Space Superiority” executive order. It set goals that included a U.S. return to the Moon by 2028, initial elements of a permanent lunar outpost by 2030, a commercial pathway to replace the International Space Station by 2030, greater use of commercial solutions in government procurement, space-security architecture reforms and development of space nuclear power.

Just as important, the order required NASA and the Commerce Department to reform space acquisitions within 180 days, with a first preference for commercial solutions and a general preference for faster contracting tools such as Other Transactions Authority and Space Act Agreements. 

Those deadlines have now passed. And we are starting to see the implementation layer show up in the real world.

• In March, the FAA completed the industry transition to its Part 450 licensing framework, which allows a single license to cover broader portfolios of launch and reentry operations and is designed to reduce administrative burden.
• On July 23, the Office of Space Commerce moved forward with a new “Space Commerce Certification” framework intended to streamline authorization for novel in-space activities such as satellite servicing, commercial stations and lunar manufacturing.
• On July 28, the FAA announced another initiative aimed at further streamlining commercial-space licensing and environmental review.
• On July 30, the Space Force said it had completed an initial acquisition-transformation plan that delegates more authority to portfolio executives and explicitly prioritizes minimum viable products, rapid iteration and commercial innovation.

That is a meaningful change from the setup at the start of the year.

The investment thesis is no longer simply that Washington wants a bigger commercial space economy. It is that the regulatory and procurement machinery is being rewired to make that economy easier to build.

For public space companies, that can translate into faster licensing, shorter sales cycles, more fixed-price and “as-a-service” contracts, and a larger pool of government demand that can reach newer entrants instead of flowing almost exclusively through traditional primes.

That is the first catalyst: policy is becoming process.

Catalyst 2: SpaceX Has Become the Sector’s Public-Market Benchmark

Back in February, the potential SpaceX IPO was the event investors were waiting for. That event has already happened.

SpaceX priced its IPO at $135 per share and closed the offering on June 15, generating roughly $85.7 billion in gross proceeds. 

That alone mattered because it gave the space sector a benchmark asset with enough scale and liquidity to force generalist investors to pay attention.

But the bigger catalyst arrived in early August, when SpaceX reported its first quarter as a public company.

Revenue surged 92% year-over-year to $7.8 billion. Starlink subscribers doubled to 12 million. Connectivity revenue reached about $4.3 billion. Enterprise and government connectivity revenue jumped 108%. And the company disclosed more than $6 billion of multi-year U.S. government awards tied largely to Starshield communications and sensing constellations.

Those numbers are important because they put hard evidence behind several pillars of the space-economy thesis at once.

• Satellite connectivity can scale to tens of millions of users and billions of dollars in quarterly revenue.
• Governments are willing to spend billions on commercial satellite architectures for communications, sensing and intelligence.
• A vertically integrated space company can capture economics across launch, satellites, services and AI rather than relying on a single revenue stream.

That is a much stronger catalyst than the IPO itself.

The IPO created attention. The earnings report created validation.

And that validation can spill across the rest of the sector – especially into smaller companies exposed to launch, spacecraft systems, power, sensors, Earth observation, intelligence and defense infrastructure.

SpaceX is still both the rising tide and the shark swimming within it. Its scale creates real competitive risk for companies that go head-to-head with Starlink, Starshield or its launch business. But for suppliers, infrastructure companies and differentiated platforms, the bigger message is that the addressable market is becoming much more tangible.

Catalyst 3: Orbital Compute Is Becoming an Actual Product Roadmap

The third catalyst is the one that sounded most absurd at the beginning of the year: data centers in space.

That idea is still early. The engineering challenges are real, including radiation, heat rejection, communications bandwidth, spacecraft lifetime and launch economics. But the narrative has moved materially closer to an investable technology roadmap.

In March, Nvidia (NVDA) formally launched its Space-1 Vera Rubin Module and other accelerated-computing platforms aimed at orbital data centers, geospatial intelligence and autonomous space operations. Nvidia said Aetherflux, Axiom Space, Kepler Communications, Planet Labs, Sophia Space and Starcloud were already using its computing platforms for next-generation space missions.

That matters because Nvidia is no longer merely profiling a startup experimenting with a GPU in orbit. It is now shipping a purpose-built space-computing platform into an ecosystem of customers and partners. 

Google is also moving forward with Project Suncatcher, its research program exploring solar-powered machine-learning compute in orbit. Google and Planet Labs are targeting two prototype satellites for launch by early 2027.

And SpaceX has gone much further. Its Starmind roadmap now describes an AI1 satellite with roughly 120 kilowatts of average compute payload, laser links through Starlink and a planned Gigasat factory designed to support production of thousands of AI satellites beginning as soon as late 2027. 

This does not mean orbital data centers are about to replace Northern Virginia or West Texas.

They do not need to.

The market only needs to believe that space-based compute is credible enough to justify prototypes, capex, launch demand and a new stack of enabling infrastructure.

And that stack is broad:

• Large-scale launch and payload deployment;
• Space-grade solar power and energy storage;
• Radiation-tolerant compute and electronics;
• Thermal management and radiators;
• Laser communications and high-bandwidth networking;
• Autonomous spacecraft operations;
• In-space servicing, assembly and manufacturing.

This is why orbital compute could matter to the space-stock trade long before it becomes a large revenue category. It creates another reason for capital to flow into the enabling stack.

Wall Street buys optionality first and waits for revenue later.

Catalyst 4: Starship Could Break the Space Cost Curve Again

Everything above ultimately depends on one variable: economics.

The space economy gets much bigger when the cost of reaching orbit goes down.

We have already seen that movie once. Reusable Falcon rockets helped collapse launch costs relative to the Space Shuttle era and enabled huge constellations such as Starlink to exist in the first place.

Starship is an attempt to do it again on a much larger scale.

SpaceX describes Starship and Super Heavy as a fully reusable transportation system. The company flew the first V3 vehicle on May 22 and completed its thirteenth Starship flight test on July 24, continuing the rapid iteration toward greater payload capacity, flight rate and reusability.

The exact future cost per kilogram remains uncertain. That is the risk. But directionally, the importance is hard to overstate.

If launch becomes dramatically cheaper and cadence rises, the economics improve for almost every downstream space business at once.

• Satellite operators can deploy larger constellations and refresh them more frequently.
• Earth-observation companies can put more sensors in orbit and shorten revisit times.
• Defense customers can build proliferated architectures with more redundancy and faster replacement cycles.
• In-space manufacturing can move from one-off experiments toward repeatable commercial missions.
• Orbital compute becomes less constrained by the mass of solar arrays, radiators, networking hardware and AI processors that must be launched.

That is the underlying flywheel of the entire thesis: cheaper launch creates more missions; more missions create more infrastructure demand; more infrastructure creates new applications; and those applications create still more launch demand.

Why These Catalysts Matter More Than Any Single Stock

This is the biggest change I would make to the space-stock thesis today.

At the beginning of 2026, it was tempting to frame the story as a list of individual winners: Rocket Lab for launch, Redwire for infrastructure, Planet Labs and BlackSky for Earth observation, AST SpaceMobile for direct-to-device connectivity.

Those company-specific stories still matter. But they are downstream of the more important question: is the space economy itself getting easier to finance, easier to regulate, cheaper to access and more useful?

Right now, the answer is increasingly yes.

Washington is making commercial activity easier to authorize and acquire. SpaceX has demonstrated commercial scale in connectivity and national-security demand. Nvidia, Google, and SpaceX are turning orbital AI into real hardware programs. And Starship is still attacking the launch-cost bottleneck that sits underneath the entire industry.

If those four trends continue moving in the same direction, the sector does not need one perfect stock pick to work. Capital can spread across multiple layers of the value chain.

The highest-beta beneficiaries will still be volatile. But that volatility is exactly why the catalyst framework matters: it gives us something more useful to watch than day-to-day stock prices.

The Updated 2026 Space Playbook: What to Track Next

If these catalysts are real, the confirmation should show up in a handful of places over the next several months:

Commercial-space regulation: watch implementation of the Space Commerce Certification framework, FAA licensing reforms and any evidence that novel missions are reaching approval faster.

Government procurement: watch NASA, Space Force and intelligence-community contract velocity, especially fixed-price, commercial and “as-a-service” awards.

SpaceX quarters: the IPO is over; the new catalyst is whether SpaceX keeps proving that connectivity, government services and launch can scale economically as a public company.

Orbital-compute milestones: watch Nvidia Space-1 deployments, Google/Planet Suncatcher progress, Starcloud missions and SpaceX Starmind hardware development.

Starship cadence and reusability: every successful flight that moves Starship closer to routine reuse improves the economic case for almost every downstream application.

Sector breadth: the healthiest signal would be rallies spreading beyond SpaceX into launch, infrastructure, Earth observation, defense and communications rather than one stock carrying the entire theme.

The Bottom Line

The space-economy bull thesis looks different today than it did at the start of 2026.

The White House executive order is no longer just a promise; implementation is showing up in licensing and acquisition reform.

The SpaceX IPO is no longer a rumor; it is the largest public-market benchmark the industry has ever had, and its first earnings report put hard numbers behind the thesis.

Orbital compute is no longer just Elon Musk talking about data centers in space; Nvidia has launched space-computing hardware, Google has prototype satellites scheduled, and SpaceX has published a product and manufacturing roadmap for Starmind.

And the launch-cost curve is still moving in the direction that matters most.

Put those together and the 2026 setup is no longer “policy tailwind + speculative narrative + future IPO.”

It is now policy execution + proven commercial scale + funded AI infrastructure + a potentially collapsing cost curve.

That is a much stronger foundation for the next space-stock breakout – and a much better framework for understanding where capital could flow next.

And if you trace where that capital is flowing right now, you’ll notice the four catalysts in this piece share one thing in common. Every single one leads back to the same man. 

The policy shift – he spent months in Washington laying its groundwork. The public benchmark – his company. The orbital compute roadmap – his product. The collapsing cost curve – his rocket.

That’s an unmistakable pattern. And I believe it’s building toward something far bigger than a strong quarter or a sector rally.

Elon Musk has been assembling this plan for nearly two decades. Now, insiders from his own biographer to the president of SpaceX expect it to reach its final form soon.

When it does, the biggest gains will come from the small, overlooked suppliers that story can’t happen without – including one trading for just $15 a share.

I’ve laid out the full picture – and your way in – right here.

The post 4 Catalysts That Could Put Space Stocks Back in Orbit in 2026 appeared first on InvestorPlace.

And that could put the Federal Reserve in a very interesting position.

Louis is joining us today to breake down the latest inflation data, what it could mean for the Fed’s next move, and why he believes the setup may be increasingly favorable for stocks.

But that’s not all he’s watching.

Louis also explains why he remains bullish on the market – including one particularly powerful area.

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

Over the past several months, the most common question we’ve heard is this:

Is it too late to buy AI stocks?

You would be right to wonder. After all, most AI stock charts now look something like this…

Intel Corp. (INTC) stock

And when the air suddenly rushes out of hot stocks, it can really go out all at once. Below is a chart of Cisco Systems Inc. (CSCO) in the aftermath of the dot-com bubble.

Cisco Systems Inc. (CSCO) stock

But here’s the thing. People ignore technological changes at their own risk. The internet did end up changing the world. And if investors had avoided companies like Cisco and bought Amazon.com Inc. (AMZN) instead, they would have turned every $10,000 invested into $30 million through today.

The AI Revolution will do the same. It will create a handful of winning companies while leaving everyone else behind.

So, the trick is to figure out which of these hot firms still have more room to run…

Or better yet, find those that Wall Street has barely even discovered.

Our three InvestorPlace Senior Analysts have done just that. In a new presentation, Louis Navellier, Eric Fry, and Luke Lango join forces to talk about their “best in class” AI portfolio of 19 companies.

These companies span a wide range of industries. Some have already risen (and have more room to grow), while others are barely starting their upward journey.

But they all have one thing in common: They are the companies propelling the AI Revolution ahead, rather than the ones getting left behind by this new technology.

Today, I have been given special permission to reveal one of these top picks. And if you want to learn more about accessing their full list of 19 stocks, click here to sign up to watch a special event they are hosting on Wednesday, August 19, at 10 a.m. Eastern.

The Next Trillion Dollar Company

In June 2026, Nvidia Corp. (NVDA) CEO Jensen Huang got up on stage at a major technology trade show and introduced the next speaker:

“The next trillion-dollar company, ladies and gentlemen,” he said, beckoning at his fellow guest.

The person he pointed at was none other than Matt Murphy, CEO of a firm our three analysts have added to their AI Revolution Portfolio:

Marvell Technology Inc. (MRVL).

And there are good reasons to be so confident in Marvell’s future.

In short, Marvell is one of exactly two companies on Earth that can build custom AI accelerators and the connections between them. These are two “superpowers” that deserve their own explanations.

Superpower 1: The Custom Engine Shop

When most people hear “AI chip,” they think of Nvidia. That’s fair. Nvidia’s graphics processing units (GPUs) are the best general-purpose AI chips that money can buy.

But “general-purpose” is another way of saying it’s the “Ford F-150 truck” of the AI world. That’s because when it comes to cars, the 4-door pickup does everything quite dependably. It’s surprisingly fast, can haul a reasonable load, and is by far the most popular vehicle in America. That’s a lot like Nvidia’s flagship “Blackwell” AI chips.

Yet, no one expects a standard Ford F-150 to do very well in a drag race. These quarter-mile sprints favor stripped-down cars that are designed to do just two things:

That perfectly describes what AI “inferencing” often needs. These types of computing tasks follow the same known path repeatedly. That makes custom chips supremely good, since they are less flexible, but extremely fast on a set track.

That’s where Marvell’s custom chips come in. The company owns a vast library of chip parts, and can assemble them like a custom engine shop building a drag racer. Together with rival Broadcom Inc. (AVGO), these two firms control roughly 95% of the custom AI chip market.

Marvell’s engineering is already serving some famous customers. It is the force behind Amazon.com Inc.’s (AMZN) Trainium AI chips, where over a million have already been deployed. And Marvell is reportedly the engineering partner behind Microsoft Corp.’s (MSFT) next-generation Maia 300 processor, expected to be revealed in September. Alphabet Inc. (GOOGL), Apple Inc. (AAPL), and Meta Platforms Inc. (META) are also customers.

That’s why Marvell’s management expects its custom chip revenue to more than double next fiscal year, and to exceed $10 billion annually by fiscal 2029.

Superpower 2: The Digital Superhighways

Now, here’s the part most investors miss.

A modern AI datacenter is not one big chip. It is tens of thousands of chips working together. And if these chips cannot communicate efficiently, it would be like running a newsroom that forces reporters to file stories with carrier pigeons. It technically works… eventually.

That makes the connections between chips just as important as the chips themselves. And this is Marvell’s crown jewel.

Marvell controls roughly two-thirds of the market for optical digital signal processors (DSPs). These are specialized chips that convert electrical signals into pulses of laser light so that data can zip between servers over fiber-optic cables. They are far faster than copper wires, and can pack more data through tiny spaces, leaving more room to add more AI chips.

Perhaps the strongest endorsement came from Nvidia itself. Rather than fight Marvell, the “king of AI” decided to adopt the technology. In March 2026, Nvidia invested $2 billion in the company so it could put Marvell’s optical chips into its proprietary NVLink Fusion ecosystem.

This business is growing more than 70% per year.

Why Buy Now?

Marvell is already a well-established player of the AI Revolution. Management expects revenues to rise 40% this fiscal year to roughly $11.5 billion, then another 45% the following year to $16.5 billion. The company has beaten estimates and raised guidance four quarters in a row, and Wall Street’s profit estimates for fiscal 2028 have surged 52% in under a year.

These are fantastic numbers.

Yet, the stock has fallen sharply since June. Shares peaked at $330 shortly after Huang’s trillion-dollar introduction, then got dragged down to the low $200s by July’s tech selloff.

That provides investors with a second chance to jump in on Marvell’s shares. I expect the stock to grind higher over the next five years and have a bull case of over $350 if AI datacenter demand materializes as expected.

One warning: Marvell’s stock is volatile. Shares have gone from $60 to $330 and back to $220 in the past twelve months. Options traders are expecting a double-digit swing in either direction when Marvell reports earnings on August 27. Volatility is the price of admission here. It’s also what keeps handing patient investors terrific entry points, just like the one July’s selloff created.

Where the AI Revolution Will Head Next

Marvell checks every box we look for in an AI winner: real customers, accelerating revenues, and a moat only one other company on earth can cross.

But it’s just one of the companies that Louis, Eric, and Luke have identified. To learn more about the stocks they like right now… where they think the AI Revolution will head next… and how investors can properly position their portfolios to play it, I recommend you click here to reserve your spot for their special event on Wednesday, August 19, at 10 a.m. Eastern.

Louis will also be announcing a major change to his role at InvestorPlace. Sign up for the event now so you don’t miss it.

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 1 Stock to Buy for the AI Revolution appeared first on InvestorPlace.

Editor’s note: “Microsoft, TSM, and Cisco Are Breaking the AI Bubble Narrative” was previously published in July 2026 with the title “The AI Capex Bear Case Just Lost Its Best Argument.” It has since been updated to include the most relevant information available.

When the first American railroads began reporting revenue in the 1840s, the critics who had called the whole enterprise an overbuilt fantasy found themselves with less and less to say.

Something similar is happening in AI right now.

Exponential View just published the most comprehensive accounting of the AI economy we’ve yet seen – its State of the AI Economy 2026 report – with real revenue, utilization, and capex payback math. 

Then Microsoft (MSFT), Taiwan Semiconductor (TSM), and Cisco (CSCO) delivered earnings that pointed in the same direction. Customers are paying for AI. Suppliers are expanding to meet the demand. And infrastructure orders keep piling up.

The tracks are still being laid. But paying freight is already moving across them.

The bear narrative now has a lot less room to breathe. 

AI Revenue Has Reached a $175 Billion Annualized Run Rate

Exponential View’s report estimates the global ex-China Generative AI (GenAI) economy is producing $175 billion in annualized revenue. And before anyone accuses Exponential View of creative accounting – this figure excludes chips, AI ad uplift, legacy software “AI features,” and financing.

In other words, it is only reflecting real customer demand.

Now, $175 billion in run-rate revenue sounds massive – and it is. But let’s contextualize that number. 

At $175 billion, the GenAI economy is already big enough to prove that real customers are paying for this technology. Revenue is scaling. Demand is showing up. The buildout is no longer running on demos and promises alone.

At the same time, AI has barely started working its way into all the industries, businesses, and daily tasks it could eventually reshape.

That is the sweet spot for investors – enough revenue to validate the thesis, with a huge amount of growth still ahead.

Because here’s the thing those relative numbers don’t capture: speed. AI revenue relative to GDP is already up 10x from Q1 2024. GenAI is scaling 3x faster than prior IT waves – faster than the internet and mobile booms. In 2023, the AI economy needed 180 days to add $1 billion of cumulative revenue. Today it needs less than two days. That is a 90x acceleration in the speed of revenue generation. Recent quarter-over-quarter growth is running ~35%, which annualizes to more than 3x.

The penetration curve is in the very earliest innings of a generational platform shift – and the data proves it.

AI Capex Is Starting to Clear Its First Payback Test

And the spending debate just got even bigger.

T. Rowe Price (TROW) technology investor Dom Rizzo believes AI-related capital spending could hit $1.6 trillion in 2027. That sits well above the current Wall Street consensus, but it shows how quickly expectations are moving.

Rizzo sees echoes of 1998, when semiconductor revenue was still climbing and the companies funding the buildout had the cash to keep going.

Bears look at a $1.6 trillion spending bill and see a bubble. The numbers are starting to push back.

The AI economy is now generating enough revenue to cover depreciation: the ongoing cost of using up the infrastructure built to run it. Not with room to spare, but the gap has closed, and the direction is positive.

For every dollar of AI infrastructure that depreciates, roughly $1.19 in hyperscaler and neocloud revenue is coming in to cover it – and $1.32 when you count the full GenAI economy. A year ago, that ratio was below 1. Now it’s above it. 

Demand on One Side, Capacity on the Other

Then Microsoft showed us where the money is coming from.

The company closed its fiscal fourth quarter with $90 billion in revenue. Microsoft Cloud grew 27% to $59.3 billion. Azure jumped 43%. Commercial revenue already under contract rose to $678 billion. And Microsoft 365 Copilot passed 30 million paid seats.

That is the demand side of the story: paying users, faster cloud growth, and an enormous amount of business already under contract.

Taiwan Semiconductor is seeing the same boom from the other side of the supply chain. The world’s leading chip manufacturer generated $40.2 billion in Q2 revenue, guided to between $44.6 billion and $45.8 billion for the current quarter, and raised its 2026 capital budget to $60–$64 billion.

Microsoft shows the customers arriving. TSM shows the suppliers racing to keep up.

Of course, none of this means every AI data center has already earned back its cost. Power, labor, leases, financing, and plenty of other expenses still have to be covered.

But the buildout has cleared its first real economic hurdle. Revenue is keeping pace with estimated depreciation, and neither customers nor suppliers are pulling back. 

The old idea that Big Tech is building a bunch of empty AI factories is getting much harder to defend.

Why Cheaper AI Can Increase Infrastructure Demand

One of the more sophisticated bear arguments has to do with token cost. Some believe that as token prices continue to collapse – with blended pricing falling from ~$17 per million tokens to ~$2 – AI companies are destroying the economics of the industry.

‘Margins are going to zero. The boom is over.’

But that argument confuses price with value – and ignores how technology adoption actually works. 

For technologies with elastic demand, falling prices create value; cheaper tokens = more use cases.

Better models expand what AI can actually do. Reasoning models consume more tokens as they think through complex problems. So the very thing bears are pointing to as a headwind – price compression – is actually the accelerant for the next leg of volume growth.

More apps, more agents, more inference, more memory, more networking, more storage, more power, more cooling, more data centers… 

The Jevons paradox – the observation that efficiency improvements in resource use lead to increased total consumption – is playing out in real time across the AI infrastructure stack.

Rizzo expects that rising usage to spread across two kinds of models: open and lower-cost systems handling as much as 80% of token volume, while the most capable proprietary models capture most of the economic value. 

The cheaper models will handle routine work at enormous scale. The premium models will take the hardest, highest-value jobs.

And either way, the chips keep running.

Why Enterprise AI Shows Up in Productivity Before Revenue

Seven in 10 AI benefits cited by S&P 500 companies involve lower costs, faster work, more output, or better quality. Only about 6% point to direct revenue gains.  The first killer enterprise AI app is not “create a magical new business line.” It’s “do the same work faster, cheaper, better.”

This is actually the normal pattern for platform shifts. The efficiency wave always comes first. Productivity gains show up in margins and labor leverage before they show up in GDP or revenue. The internet’s first decade was dominated by cost reduction and efficiency. Revenue came later – and when it came, it was enormous.

AI is following the same path: efficiency first, new revenue later. And if the efficiency wave alone is already supporting $175 billion in annualized demand, the next phase could be much larger. 

What This Means for AI Stocks

The macro data on AI has never been more bullish. The micro data – real company revenues, utilization trends, and capex payback – is inflecting positively. And yet AI stocks have been choppy, volatile, and in some cases well off their highs.

That combination – improving fundamentals, weak stock prices – is the definition of a buying opportunity.

Cisco’s latest quarter offers a fresh example. Networking revenue rose 28% year over year, while AI infrastructure orders reached $9.3 billion for fiscal 2026. Its shares still fell as investors focused on narrower margins. Demand is real, but Wall Street is becoming more selective about which companies can turn that demand into lasting profits. 

The names best positioned to benefit from this data are across the full AI Builder stack:

• Chips and semiconductors
• Memory
• Networking and optics
• Servers and infrastructure
• Power and cooling

The Bottom Line: AI Revenue Is Starting to Catch the Capex

For the past two years, the biggest question surrounding AI was if this technology would ever make enough money to justify all the spending.

We are starting to get the answer.

Exponential View’s math shows AI revenue now covering estimated infrastructure depreciation. Microsoft is turning AI into faster cloud growth, paid Copilot seats, and a massive contracted backlog. TSM is expanding capacity to keep up. Cisco is booking billions in AI networking orders.

And one respected technology investor now believes annual AI spending could reach $1.6 trillion in 2027.

There are still real risks. Some projects will disappoint. Margins will get squeezed. Financing costs and valuations will matter.

But the simplest version of the bear case – that nobody would pay enough for AI to support the infrastructure underneath it – is losing its footing.

That does not make every AI stock a buy. It makes choosing the right stocks, fitting them together, and deciding how much capital each one deserves even more important.

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

We also assigned a recommended allocation to every holding, so investors can see how we think the positions should fit together and how much each idea deserves.

We’ll be unveiling this newly rebuilt portfolio this Wednesday, August 19. Join us to see which stocks made the cut.

The post Microsoft, TSM, and Cisco Are Breaking the AI Bubble Narrative appeared first on InvestorPlace.

In the 1989 film Field of Dreams, the famous line goes: “If you build it, they will come.” But in the AI boom, the saying may need an update:

“If you build it, communities will protest. But if you have already built it, they may come.”

The “it” here is data centers. As AI firms race to build more data centers, communities are increasingly pushing back against new projects.

On July 18 alone, 142 protests took place across 42 states in the first nationwide protest effort against the rapid expansion of AI data centers. And Data Center Watch reports that at least 75 U.S. data-center projects worth about $130 billion were blocked or delayed in the first quarter of this year.

At the same time, AI’s appetite for computing power continues to grow. That brings us to the “they” – AI companies desperate for more computing power.

A simple supply-and-demand problem is happening here: New capacity is becoming harder to build just as demand for AI computing continues to soar.

And that imbalance is creating a new opportunity.

When new capacity becomes harder to build, existing capacity becomes more valuable. And companies that already have the land, power and facilities needed for AI data centers could be sitting on valuable real estate – literally.

And a deal made this week between AI giant Anthropic and an unlikely infrastructure provider offers a glimpse of what that opportunity could look like.

So, in today’s Smart Money, I’ll take a closer look at that deal to show you how one AI bottleneck can create opportunities across multiple industries. Then, I’ll reveal how we’re positioning for those very opportunities.

AI Buys What’s Already Built

On Tuesday, Anthropic reportedly signed a 20-year, $9.1 billion deal with Riot Platforms, Inc. (RIOT) for 191 megawatts of data-center capacity at Riot’s Rockdale, Texas, campus. Riot expects the deal to generate about $9.1 billion through 2048, with an option that could push the total value to $16.1 billion. The capacity is expected to be delivered in phases, beginning in 2026 and continuing through 2028.

The key here is that Riot doesn’t have to start from scratch. The company, best known as a bitcoin miner, already has the land, power and infrastructure needed to support a data center. So, instead of using all of that capacity for bitcoin mining, it can lease it to AI companies, like Anthropic.

Riot already struck a deal with Advanced Micro Devices Inc. (AMD) for up to 200 MW of data-center capacity earlier this year. The Anthropic deal takes that strategy much further.

As demand for computing power rises and new data centers become harder to build, sites that already have power and infrastructure could become increasingly valuable, even if they were originally built for something completely different.

Anthropic and Riot’s billion-dollar-deal shows how much AI companies are willing to pay for capacity they can actually access. But the bottleneck doesn’t stop at data centers. Building all this AI infrastructure requires a massive amount of power, equipment, and raw materials.

It reaches all the way down to the materials and equipment needed to build them.

That means AI’s rapid growth is creating investment opportunities at every rung of the AI ladder…

The Ladder of Opportunity

One single stock, industry, or sector simply can’t capture the entire opportunity. For instance, the technology needs:

Power generation – AI data centers need enormous amounts of electricity, and power producers supply it. As AI drives demand for new data-center capacity, companies that generate and sell that electricity can benefit.

Grid infrastructure – Data centers also need to connect to the power grid. Companies supplying transformers, substations, transmission equipment and other grid infrastructure are helping make the AI buildout possible.

Cooling – AI chips generate enormous amounts of heat, making cooling systems essential to keeping data centers operational. Companies providing liquid cooling, HVAC, and other thermal-management systems are well-positioned to benefit from the expansion of AI infrastructure.

Construction – Someone has to build all those data centers and power facilities. Construction and engineering companies that design and construct the infrastructure are another part of the opportunity.

Semiconductors – Companies like Nvidia Corp. (NVDA) supply the chips that provide the computing power AI systems require, making semiconductors a core part of the physical infrastructure behind the AI boom.

Memory – AI systems also require enormous amounts of DRAM, HBM, and other memory. So, memory manufacturers are supplying another critical component of the computing infrastructure needed to scale AI.

This is a bottleneck we’ve recently discussed here at Smart Money.

In all, the AI Revolution has created an enormous number of potential investment opportunities. But the more this technology spreads, the harder it becomes to know which companies deserve your attention – and, just as importantly, which don’t.

Separate the Best From the Rest

There are now so many ways to invest in AI that simply finding an AI stock isn’t enough. The challenge is separating the best opportunities from the rest.

That’s why my InvestorPlace colleagues Louis Navellier, Luke Lango and I have gone back through our AI research and narrowed our recommendations into a newly rebuilt portfolio, the AI Revolution Portfolio.

We first launched this portfolio back in 2023 to narrow the huge universe of AI-related companies down to what we considered the best-in-class opportunities. By combining our different investing strengths, we designed a portfolio that captures multiple parts of the AI ecosystem, rather than betting everything on one company.

And we’ve rebalanced it at pivotal moments in the AI Revolution. For instance, in 2024, AI developers were reaching the limits of brute-force improvements, creating a divide between companies that could adapt and those that couldn’t. So, in December of that year, we rebalanced our AI Revolution Portfolio to make sure we were positioned on the right side of that divide.

Since that rebalance in December 2024, our portfolio has risen 58% – more than double the Nasdaq Composite’s 25% return and nearly triple the Dow Jones Industrial Average’s 19% gain.

Now, we’re at another pivotal moment, where a single AI bottleneck could create opportunities across multiple industries.

We’ll be hosting a special event next Wednesday, August 19, at 10 a.m. Eastern to unveil our new portfolio and show you exactly how we are positioning for AI’s next phase. Click here to reserve your spot now.

In other words, we’ve rebuilt it. Now, all that’s left is for you to come.

Simply click here to join us. We look forward to seeing you there.

Regards,

Eric Fry

The post AI’s $130 Billion Problem – and the Portfolio Created to Solve It appeared first on InvestorPlace.

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.

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.

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.

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.