Despite the adverse impact of the novel coronavirus, AI stocks have fared relatively well. Consider the Global X Robotics & Artificial Intelligence (NASDAQ:BOTZ) ETF. For 2020, the fund has returned about 6%.
The interesting thing is that until about 10 years ago or so, AI was mostly a backwater. Let’s face it, investors were more interested in areas like cloud computing.
But there would emerge some major catalysts that would make AI a must-have. There were the breakthroughs in the underlying algorithms, such as deep learning. They would lead to vast improvements in accuracy — making it possible for much better image and facial recognition systems.
It also helped that there was substantial growth in the availability of data as well as the ubiquity of open-source tools, which made it easier for anyone to create AI models.
OK then, so when looking ahead, what are some of the interesting AI stocks that should continue to benefit? Where are the opportunities? Well, let’s take a look at seven.
Note: For the Money Show, I will be giving a virtual presentation called “Artificial Intelligence: What Investors Need to Know” on Wednesday, June 3, from 3:50 p.m. to 4:20 p.m. eastern.
- Netflix (NASDAQ:NFLX)
- Alphabet (NASDAQ:GOOGL)
- NVIDIA (NASDAQ:NVDA)
- Microsoft (NASDAQ:MSFT)
- Alibaba Group (NYSE:BABA)
- Alteryx (NYSE:AYX)
- Dynatrace (NYSE:DT)
AI Stocks: Netflix (NFLX)
Netflix has come a long way since its founding in 1997, when the company was focused on distributing DVDs through the mail. Of course, now it is the global leader in streaming and has a market value of $185 billion. And a big reason for this has been the heavy investments in AI.
This has not just been about hiring smart engineers. Keep in mind that — back in 2006 — the company set up a $1 million contest to see who could build a better algorithm for movie recommendations!
While many AI stocks have other segments that do not rely on the technology, this is not really the case with Netflix. At the core of the company is a recommendation engine that is powered by a set of sophisticated models that somehow know what shows people want to watch.
To get a sense of how extensive this is, consider the thumbnails that appear when there is a search. Note that these are not static visuals of the movie or TV show. Rather, an AI system scans each frame and finds the image that has the most impact.
But Netflix has leveraged the technology for other key areas of the business. Here are just some of them:
- Improving the speed of the streaming
- Finding the right locations to shoot scenes
- Recruiting the best talent — based on the budget
- Personalizing marketing messages, such as with email campaigns
True, Netlfix has much more competition to deal with, such as from Disney (NYSE:DIS), AT&T (NYSE:T), Comcast (NASDAQ:CMCSA) and Apple (NASDAQ:AAPL). But the company has some big advantages, like an AI-driven culture, extensive data sets and proven algorithms.
The company has also shown an ability to keep up the growth ramp, as it added 16 million subscribers in the latest quarter.
Alphabet (GOOG, GOOGL)
Back in 1998, when Larry Page and Sergey Brin founded Google, there was little talk about AI stocks. At the time, investors were obsessed with dot-coms.
Yet Google was actually very much an AI company. When Page and Brin were getting their Ph.D.’s at Stanford, they were studying futuristic ideas like autonomous cars. But as for Google, the search engine was also based on a sophisticated machine-learning algorithm that found patterns in huge amounts data.
As the company grew, there was more innovation on AI, such as to build tools to help create stronger models. This would ultimately become TensorFlow, which Google open sourced in late 2015.
Then there were a myriad of acquisitions in the AI space. One of the most notable was for DeepMind, one of the most cutting-edge firms in the space. For example, its AlphaGo system was able to beat the leading Go champion. This was certainly an amazing feat, since the game has far more potential moves than chess.
Google also has Wayme, one of the most advanced autonomous driving operations. The cars have logged more than ten million miles across public highways and there is also a ride-sharing service.
In light of all this, is it any wonder that Google CEO Sundar Pichai says that the company has an “AI first” strategy? Definitely not. It’s also a strategy that should help keep up the growth in the years ahead.
Regarding AI stocks, the attention is often on software. Yet hardware is critical — and also a lucrative market.
A standout player in the segment is Nvidia. Founded in the early 1990s, the initial focus was on the gaming market. The core technology, called the GPU (Graphics Processing Unit), allowed for more immersive graphics.
But interestingly enough, the technology would also prove effective for AI applications. The main reason: the chips make it possible for parallel processing at high speeds. For example, a CPU-based platform may train a sophisticated AI model in months while a GPU could do it in days or weeks.
Through much of Nvidia’s history, the strategy has been to build the technology in-house But this is starting to change. Consider that the company recently shelled out $6.9 billion for Mellanox. Founded in 1999, the company has become a leader in building systems for high-compute environments, such as in the data center. This is definitely critical for AI development. So yes, the deal should help supercharge Nvidia even more.
In the latest earnings call for Nvidia, CEO Jensen Huang said: “The basic computing elements are now storage servers, CPU servers, and GPU servers and are composed and orchestrated by hyperscale applications that are serving millions of users simultaneously. Connecting these computing elements together is the high performance Mellanox networking. This is the era of data center scale computing and together, Nvidia and Mellanox can architect end-to-end.”
When it comes to AI stocks, Microsoft is certainly not a pure-play for the technology. But CEO Satya Nadella has been working hard to retool with existing applications and platforms. It’s smart that he first made sure to create a robust cloud infrastructure, allowing for centralization of data. While Amazon (NASDAQ:AMZN) remains the leader, Microsoft is now No. 2 and continues to gain momentum.
Now, the company does have some inherent advantages for AI. Microsoft has a massive base of corporate customers, huge data repositories and thousands of talented engineers in cutting-edge research and development. The company has also been willing to make big bets, as seen with acquisitions of LinkedIn and Github.
Yet perhaps the most important key, though, is the willingness to take the long view. Just look at the $1 billion investment in OpenAI, whose mission is to build “Strong AI” systems. This involves innovations where machines can be creative and make sound judgments.
But to make this a reality, there needs to be enormous computing power. To this end, Microsoft and OpenAI have partnered to build an Azure-based supercomputer, which is one of the top five in the world. It has more than 285,000 CPU cores and 400 gigabits per second of network connectivity for each GPU server. With this, it is possible to train models with billions of parameters.
According to a quote from Microsoft Chief Technical Officer Kevin Scott in the Microsoft blog: “This is about being able to do a hundred exciting things in natural language processing at once and a hundred exciting things in computer vision, and when you start to see combinations of these perceptual domains, you’re going to have new applications that are hard to even imagine right now.”
There are definitely solid AI stocks outside the U.S. In fact, China is one area that has many of the leading companies. Then again, the government has made AI a strategic priority. There are is also a thriving venture capital ecosystem, large numbers of talented engineers and researchers, and massive data sets (hey, the population is 1.4 billion).
No doubt, a leader is Alibaba. The company has leveraged its large ecommerce user bases to develop innovative systems for better personalization and logistics. It also has Alime, which is a digital assistant similar to Alexa. This has been backed up with a $1.15 billion commitment to invest in the smart speaker market.
But Alibaba has also been innovating with chip technologies. The company’s Hanguang 800 has shown much promise with AI model development.
And another factor to keep in mind is that Alibaba is rapidly becoming a cloud power. It has seen how important this aspect has been for AI with companies like Amazon and Microsoft. As a result, Alibaba plans to invest about $28 billion in its own cloud business for the next three years.
Without data, there is little you can do with AI. But data is often a major pain point. Simply put, it’s difficult to find enough of it. As a result, data can easily consume 80% of the time for creating AI models.
But this presents a great opportunity for a company like Alteryx. Founded in 1997, it has built one of the top platforms for data. But it goes well beyond just providing access to different sources across an organization. Alteryx makes it easier for business people — who do not have data science backgrounds — to build their own analytical and AI models. It’s often as easy as drag-and-drop. The vision of Alteryx is to allow for the so-called “citizen data scientist.”
The company is continuing to grow at a rapid pace. In the latest quarter, revenues jumped by 43% to $108.8 million and the operating cash flows came to about $20 million. Just some of the company’s customers include Audi, Vodafone and McDonal’s (NYSE:MCD).
Dynatrace is one of the smaller AI stocks, with the market capitalization at a little over $10 billion. But the growth potential looks bright.
The company’s systems help enterprises to better manage the complexity of their IT environments. Here’s how Dynatrace explains it in its latest 10-K filing: “Our platform utilizes artificial intelligence at its core and continuous automation to provide answers, not just data, about the performance of applications, the underlying hybrid cloud infrastructure, and the experience of our customers’ users. We designed our software intelligence platform to allow our customers to modernize and automate IT operations, develop and release high quality software faster, and improve user experiences for better business outcomes.”
Then how big is the opportunity? Based on a recent investor presentation, the TAM (Total Addressable Market) is more than $20 billion. To put this in perspective, Dynatrace’s annual revenues are $545.8 million. So there is still quite a bit of room left for growth.
Tom Taulli (@ttaulli) is an advisor and author of various books and online courses about technology, including Artificial Intelligence Basics, The Robotic Process Automation Handbook and Learn Python Super Fast. He is also the founder of WebIPO, which was one of the first platforms for public offerings during the 1990s. As of this writing, he did not hold a position in any of the aforementioned securities.