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We fundamentally believe we are entering the “Age of AI” and that this new age represents the biggest wealth-creation opportunity the world has ever seen.
Sounds hyperbolic. It’s not.
We’re confident that the next decade will be defined by the emergence of new AI technologies that will reshape every facet of our global economy, much in the same way the 2010s were defined by the emergence of internet technologies that entirely reshaped our global economy.
In the 2010s, retail stores became e-commerce sites. And in the 2020s, e-commerce sites will evolve into AI-driven marketplaces, with machine learning (ML) algorithms powering product recommendations and pricing dynamics.
In the 2010s, video rental and music stores became streaming platforms. And in the 2020s, streaming platforms will be run using AI, with ML algorithms powering content recommendations.
In the 2010s, networking parties and social outings became social media apps. And in the 2020s, social media apps will be powered by AI, with every feed, post, comment, video, and friend recommendation delivered to you in a hyperpersonalized fashion.
Even things like energy infrastructure, electric vehicles, and drug discovery will be propelled forward by AI as we use ML algorithms to optimize energy usage and storage on the grid, employ endless chemistry simulations to create more efficient batteries, and create better genetic mapping to diagnose and treat diseases more efficiently.
AI will change everything over the next decade.
And much like the internet, it will mean fortunes and empires for some folks – and broken dreams and empty bank accounts for others.
The internet gave birth to Amazon, Alphabet, Microsoft, and Apple. It also laid waste to Sears, JCPenney, RadioShack, Blockbuster, and Polaroid – each of which were, in their heyday, considered titans of corporate America.
The Age of AI will do the same. It will create new multi-trillion-dollar empires – and destroy seemingly indestructible ones.
But it will do so on a scale greater than any we’ve ever seen.
According to the World Economic Forum, the global digital economy measured about $14.5 trillion in 2021.
That’s huge. But it is nothing compared to the size of what the AI Economy will be one day.
According to PricewaterhouseCoopers (PwC), the AI Economy will grow to $15.7 trillion by 2030 – and that’s one of the more conservative estimates out there. The folks over at ARK Invest believe that at 100% adoption, the global AI market could be worth about $200 trillion (PDF).
Both agree that the AI market will most likely be worth around $15 trillion by 2030.
But they also see a bull-case scenario for the market growing to $40 trillion by 2030 and, further, think that at 100% adoption, the global AI market could be worth about $200 trillion!
This is the biggest, most important technological revolution of our lifetimes, with the biggest economic stakes of any paradigm shift we’ve ever witnessed.
Why else do you think Microsoft, Alphabet, Tesla, and others are racing toward AI supremacy?
All of those companies were pretty quiet about AI for years, until ChatGPT’s unveiling. Within months, Alphabet launched a competitor, and Tesla started calling itself the biggest AI company in the world.
That’s no coincidence.
These tech giants know that everything is at stake in the emerging Age of AI.
If Alphabet doesn’t create the best AI-powered search platform, it won’t be the world’s most used search engine in 10 years.
If Amazon doesn’t create the best AI-powered e-commerce platform, it won’t be the world’s largest retailer in 10 years.
The stakes are high. So are the potential rewards.
And that’s why we aren’t running away from AI – we’re embracing it.
At this point, it’s time to delve deeper and discuss the two main classifications of AI programs.
AI is known to be either narrow or general.
Narrow AI is an AI system trained on a particular category of data and designed to perform a specific task or set of tasks within the same category as its training data. General AI, on the other hand, is an AI system trained on any category of data and able to perform any intellectual task that a human can do.
Narrow AI is programmed to recognize patterns and perform tasks based on predefined rules and algorithms. It is very formulaic and mathematical. And general AI is capable of reasoning, understanding complex concepts, and learning from experience. It can adapt to new situations and solve problems that it has not encountered before.
Narrow AI exists today, evidenced by voice assistants like Siri and Alexa. Those narrow AI systems are trained on voice data to perform tasks within their domains of expertise.
ChatGPT is a narrow AI system that is trained on text data to perform prompt-activated tasks within its domain of expertise.
Now, narrow AI systems have their limits. ChatGPT can’t pick winning stocks for you. But it can do what it is programmed to do – give answers to general-knowledge questions – very well.
To be sure, general AI does not exist today. Based on our conversations with AI industry experts, it is our conclusion that general AI will assuredly not exist within the next decade and is even unlikely to materialize within the next 20 to 30 years.
That’s because the technologies and algorithms we are using today to create narrow AI systems do not translate to a better understanding of general AI and likely will not help us to create it. The general AI problem is a very complex one and likely won’t be solved anytime soon.
That’s entirely fine with us, though, because general AI is somewhat spooky – even to forward-thinking folks like us.
It’s the AI you see most often in science-fiction movies, like Jarvis from Iron Man or HAL 9000 from 2001: Space Odyssey. Those movies pose interesting questions as to the self-perceived motives and purposes of general AI, and those are deep, complex questions that need to be answered before we truly develop general AI.
But those are questions that can be answered another day… or, rather, another decade since general AI is nowhere close to becoming a reality.
Instead, the emerging Age of AI in the 2020s will be centered around the development and deployment of sophisticated narrow AI systems.
That is why our strategy for the coming AI boom revolves around investing in what we believe will be the developers of the highest-quality, highest-impact, and most-scalable narrow AI systems in specific sectors of the economy.
To do this, we have created a narrow AI “focus list” of sectors where we think those systems will have the biggest impact over the next three to five years. In each of those sectors on our list, we have highlighted the most interesting companies that we feel are poised to develop the best narrow AI systems in the industry.
Narrow AI systems have huge potential in the world of cybersecurity, where they can be used to automate and optimize network monitoring, logged events, intrusion detection alerts, etc. Moreover, AI will need to be deployed across the cybersecurity world because hackers will assuredly start leveraging AI to create hyper-fast malware that will require AI-powered security systems to detect and stop them promptly. We see AI becoming a ubiquity in the world of cybersecurity by the end of this decade.
Companies to Watch: We think SentinelOne (S) is the leader in AI-powered cybersecurity. Its novel and proprietary behavioral AI platform allows it to use AI to identify network behavior anomalies. However, we recently placed S stock on “Hold” due to disappointing guidance in its latest earnings report. We’re not sure exactly what is driving the weakness, but hold off on buying shares of SentinelOne until we can properly analyze the situation. Otherwise, we think Palantir (PLTR) also has great upside potential through cyber AI. The company has constructed the world’s best data science platform, which is already widely used today by the U.S. government for cybersecurity purposes. As those entities upgrade their defenses with AI, they will almost certainly use Palantir’s data science platform to drive those upgrades.
We’re really excited about the application of AI in the programming world. It’s already being used to optimize code, detect bugs, manage version control systems, test automation, and even write code from scratch. These efforts are all in their early stages, but they have the potential to save a significant amount of time and energy in the coding process. And since everything is seemingly built on top of code these days, the ability to achieve significant time and cost savings in code generation and maintenance could, by extension, unlock significant economic value. This is a total game-changer and one of the most exciting near-term AI investment opportunities.
Companies to Watch: GitHub Copilot is the most popular and widely-used AI programming tool in the market today, and GitHub is owned by Microsoft, so here we see yet another reason to own MSFT stock for the coming AI boom. However, GitLab (GTLB) is making successful inroads in the AI programming world as well. That stock is really interesting for the long term. We do not own it in our portfolios because the valuation has been too rich for our taste, but this is certainly a name we’d consider on significant weakness.
We don’t like to pick favorites, but if we had to pick our favorite narrow AI investment theme for the next three to five years, it would be robotics AI. This includes the integration of narrow AI systems with narrow robotics systems to create real-world automation solutions. We’re talking robotic kitchens, warehouses, cleaners, cars – robotic everything. The first wave of robotics will be mostly low-level (robots automating mundane tasks), and that’s where our investment focus lies these days. We believe these solutions are ready to have a major impact today and will see huge, rapid adoption into 2025.
Companies to Watch: The king of the hill here is Symbotic (SYM), with its end-to-end warehouse automation solution that Walmart (WMT) is fully adopting. But we see huge potential for Toast (TOST) to start integrating robotics into its full-suite solutions to optimize restaurant operational efficiency as well. In the private world, we like what Miso Robotics is doing. It’s making burger-flipping robots – and we actually think a partnership between Miso and Toast would generate huge synergies. Of course, we’re also very bullish on the emergence of semi-autonomous vehicles over the next one to three years, with our favorite investment in this space – Luminar (LAZR) – just snagging a huge multi-billion-dollar contract to supply sensors to Mercedes-Benz (MBGAF).
Narrow AI systems can be deployed in a variety of ways across the energy industry to reduce costs and improve operational efficiency as well. Some examples include predictive maintenance, wherein AI is used to analyze sensor data and predict when equipment maintenance is needed, and energy demand forecasting, wherein AI is used to analyze historical energy consumption data and predict future energy demand. AI is also used to optimize solar and wind energy production through weather prediction and optimizing grid load. If 2022 taught us anything, it is that the world needs to massively upgrade its multi-trillion-dollar energy infrastructure. And AI is the upgrade it needs.
Companies to Watch: Interestingly enough, maybe our favorite pick here is Samsara (IOT) because it is the leader in predictive maintenance with its Connected Cloud platform. We also very much like C3.ai (AI), as the company has successfully cut out a niche for itself supplying enterprise AI solutions to the oil and gas industry. Energy storage firms Stem (STEM) and Fluence (FLNC) are also beneficiaries of the energy AI movement, as both leverage AI for grid optimization.
