Dear Readers,

Three engineers, $600, and a booth at Denny's - that's all it took to plant the seed for what is now a $4.6 trillion empire sitting at the very heart of the AI revolution. Today's deep dive traces NVIDIA's full arc: Near-bankruptcy in the 1990s through the quiet, decades-long CUDA coding model bet that Wall Street ignored, to the AlexNet moment which changed everything, and finally to the staggering growth that define the company today. These are: $130.5 billion in revenue, 88% of it from data centers, and gross margins that make any CEO jealous.

We break down the triple moat that makes NVIDIA so extraordinarily hard to dethrone, examine whether AMD and Intel have any realistic shot at closing the gap, and ask the uncomfortable question: what happens to gaming when your GPU maker decides AI is the real business?

Plus, in Chubby's Opinion Corner, we look beyond the earnings reports to consider what NVIDIA's dominance actually means for the world - from industrial-scale intelligence to the geopolitical landscape of compute. This one's a full story, decades in the making, and it starts right now.

All the best,

Jensen Huang: “And so we would meet at Denny’s, which is right at the corner of Capitol and Berryessa, this place in East San Jose. I used to wash dishes at Denny’s and I was a busboy at Denny’s, and I was a waiter at Denny’s. So I really liked Denny’s. I mean, Denny’s, I consider it my first company, you know, and so, we would go hang out there. It was always a fun thing for me and a fun thing for them. We’d just sit there and, you know, drink a bunch of coffee, and the thing that’s really great about Denny’s is it’s all you can drink.”

Chris Malachowsky: ”We’d show up, we’d order one bottomless cup of coffee. And then, you know, work for four hours.” (The NVIDIA founders on their beginnings; https://sequoiacap.com/)

NVIDIA’s ascent is often told as if it were sudden: one day it was “the gaming GPU company,” and the next it became the essential supplier behind the generative AI boom. But that version of their story is way too simple - and it misses what is actually most interesting. NVIDIA’s current position was not created in a single ChatGPT moment. It was built over decades through a sequence of technical bets, platform decisions, and an unusually consistent strategic vision around accelerated computing. (NVIDIA itself now describes the company as a “full-stack computing infrastructure company,” which is a revealing phrase.)

In January 1993, three engineers pooled $600 in startup capital at a Denny’s restaurant in San Jose, California, and decided to build a company around 3D graphics. Jensen Huang was 30 years old. His co-founders, Chris Malachowsky and Curtis Priem, shared a conviction that accelerated graphics would become essential for gaming and multimedia. NVIDIA first became a household name in PC gaming, especially after the company’s GPU breakthroughs in the late 1990s and the rise of the GeForce brand. That gaming success gave NVIDIA revenue, the power of brand, and, just as importantly, a demanding user base that rewarded raw performance improvements year after year. In hindsight, gaming was not a detour before AI. It was the proving ground that forced NVIDIA to build the engineering culture, chip design cadence, and software habits that later became decisive in AI. Yet here we are. In fiscal year 2025, NVIDIA posted $130.5 billion in revenue - nearly five times what it earned just two years earlier. Its market capitalization has surpassed $4.61 trillion (february 2026). And the engine behind that meteoric rise is not gaming, but artificial intelligence. Data center chips, the hardware that trains and runs AI models like ChatGPT, now account for roughly 88% of NVIDIA’s total revenue. The gaming division that built the company? It still exists, is still profitable, is still dominant in its market - but has become a side story to a much larger narrative.

Therefore, the central question is not simply how NVIDIA “moves from gaming to AI,” but whether NVIDIA was already building an AI company long before the market realized it. If that is true, then the company’s dominance is less a lucky wave ride and more the result of a rare combination: timing, technical depth, and a management team willing to invest early in an ecosystem that did not yet have mass demand. The evidence strongly suggests exactly this.