The Hidden Winners of the AI Megatrend VIEW IN BROWSER
By Jeff Brown, Founder, Brownstone Research A chart landed on my desk recently that made me stop cold. It showed global AI computing capacity over the past three years. For most of that time, the line crawled along at a steady angle – predictable, linear, unremarkable. Then, in early 2024, it went nearly vertical. It plotted what exponential growth looks like in real time. And most people completely miss it because our brains aren't wired to grasp exponential curves. We think in straight lines – gradual, steady, proportional. Exponential growth tends to feel flat and boring… right up until it doesn't. But that inflection point – that sudden leap from gradual to explosive – is where fortunes get made. It's also where most investors get left behind because they're still thinking linearly while the world moves exponentially. At Brownstone Research, identifying exponential growth – right before it goes vertical – is one of our specialties. Wherever there is exponential growth, you can bet we’re neck-deep in it – researching and providing our subscribers with the insights and investment recommendations designed to capitalize on these trends. Right now, AI computing capacity is the exponential growth engine fueling everything happening in AI right now. And if you don't understand this underlying trend, you can't possibly understand where the real opportunities are hiding. Today, I’ll show you that chart that stopped me in my tracks so you can see exactly what I mean. Then, you’ll find out where the opportunities best positioned to capture that growth are hiding – and why now is the time to act. The Truth About AI Compute The chart below puts a visual to the current trends driving AI’s exponential growth. It graphs the global artificial intelligence (AI) computing capacity since the first quarter of 2022. And it shows how it has grown over time. When I say “computing capacity,” I’m talking about the raw processing power needed to run AI – the electricity and muscle it takes to let the AI “brain” think. The chart compares five companies' chip offerings using a common yardstick: One unit of compute equals a single NVIDIA (NVDA) H100 GPU, the industry-standard chip used to power AI workloads. 
You can see the inflection point that happened around early 2024, when the curve starts to go vertical. This is a classic example of exponential growth. In this case, it is the exponential growth of global AI computing capacity. And this capacity is directly related to breakthroughs in artificial intelligence. When GPT-4 launched in 2023, it could reason across complex problems with a simple prompt. By early 2024, increased computing capacity allowed AI models to process entire books, codebases, and legal documents in one pass. When computing power scales, innovation doesn’t just move in a straight line – it leaps. Exponentially. But here’s the key point that’s equal parts exciting and anxiety-inducing: The above chart shows us that global AI computing capacity is doubling every seven months. And that was as of the third quarter of 2025. This growth has only compounded since then. If I had to estimate, we’re now doubling capacity every six months. But here’s where the context is important… Double the Capacity in Half the Time Moore’s Law, which became the reference example for exponential growth, showed that engineers could keep squeezing more computing power onto a single chip by packing in more microscopic transistors. Moore’s Law accurately predicted a doubling every 18-24 months. And that steady doubling drove decades of tech innovation. Today, AI is following a similar – but even steeper – curve. Instead of just packing more transistors onto one chip, companies are linking together tens of thousands of advanced GPUs in massive data centers. The result isn’t incremental progress. It’s sudden leaps in capability. One year ago, global AI computing capacity was doubling at a pace of about every 10-12 months. Think about that. In just a year, the time it took to double AI compute capacity has nearly been cut in half. From an investment standpoint, the real story is happening underneath the fold here. Because when compute doubles every six months, it creates cascading demand across the entire ecosystem. The Foundation Beneath the Models Every incremental jump in AI capability requires: - More advanced semiconductors
- Higher-performance GPUs
- Custom AI accelerators
- Massive data center buildouts
- Power generation and grid upgrades
- Cooling systems
- High-bandwidth networking
- Advanced software orchestration
If we look at it holistically, AI is fundamentally an infrastructure story. And infrastructure is where many of the greatest fortunes are made. This is where the concept of Secret AI Stocks becomes critical. The most obvious AI companies – the hyperscalers and model developers – get the headlines. But the hidden winners are often the companies supplying the bottlenecks. This is why the biggest opportunity in artificial intelligence no longer lies in buying the companies building the most famous models. Instead, it’s about identifying the companies that: - Enable compute expansion
- Optimize performance
- Translate raw compute into real-world applications
- Provide the modeling infrastructure for entire industries
As AI compute scales exponentially, the demand for specialized platforms and domain-specific AI tools grows alongside it. In life sciences, for example, AI-powered modeling platforms can reduce years of trial-and-error experimentation into weeks of simulation. In drug development, advanced compute enables faster candidate screening and predictive toxicity modeling. In manufacturing, it enables real-time optimization of complex systems. And then there’s the big one – energy. Powering this rapidly expanding capacity requires an enormous amount of electricity. And that electricity must be physically produced. What we’re talking about here are the hidden beneficiaries of exponential capacity growth. That’s where we find the Secret AI stocks that don’t make the headlines. On the surface, these plays don’t look like AI stocks at all. But they’re perfectly positioned to become the next trillion-dollar AI mega caps. To identify the Secret AI Stocks with the biggest profit potential, I teamed up with TradeSmith’s own Jason Bodner. Where I find these stocks through my Silicon Valley network and deep technology expertise, Jason finds them through institutional buying patterns and quantitative analysis. When we started comparing notes, we realized we were both seeing the same stocks from completely different angles – and knew we had something special. Tonight, we’re revealing a brand-new system that targets stocks just like these… the under-the-radar AI plays that most investors aren’t aware exist. We’ll reveal a system for spotting these plays that’s already pinpointed moves as high as 601%, 1,921%, 1,940%, and more during testing. And as a bonus, we’ll each reveal one pick during the live webinar, which airs tonight at 8 p.m. ET. All you have to do is click here to register automatically and reserve your seat. Regards, Jeff Brown
Founder and CEO, Brownstone Research In Case You Missed It 
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