Meeting Jensen Huang from NVIDIA

You gotta love this company. Why? Because it’s the backbone of today’s AI explosion. ✨🚀

The silicon brains behind #ChatGPT. The processing tornado behind many high-end graphics processing, simulations, games, renderings… you name it.

What impressed me the most when meeting Jensen Huang yesterday, who founded NVIDIA exactly 30 years ago, April 5th 1993, was his humility and grounded experience. Starting with two other partners and just $40,000 back then, working their way through the industry as a no name, and eventually hitting milestone after milestone. At the turn of the millennium, late 1999, they launched their famous GeForce graphic cards series, later struck a record-breaking deal with Xbox, followed a few years later with a collaboration deal with Sony’s PlayStation. The late 2000’s saw rougher waters ahead with product instabilities and legal battles with various industry competitors, but 2011 bringing this phase to a closure with, e.g., a $1.5 billion cross-licensing agreement with Intel. Again, a crisis bringing further opportunities.

Today, NVIDIA is no doubt a computing powerhouse. As Jensen repeatedly elaborated: “accelerated computing, not parallel computing.” This was the guarantee for their survival and growth. Not to provide additional chips to offload computing and run parallel with CPUs, the heavy loaded, legacy burdened and highly complex main processing core of computers. But following the strategy of "accelerating" by augmenting certain processing applications and focusing purely on accelerating the whole vertical process. As Jensen points out: “That gave us control of the full stack, something that a normal CPU cannot.” Owning a vertical processing stack gives unprecedented advantage for scaling. And NVIDIA is proof of that.

Now valued $1.05 trillion, NVIDIA’s market cap is a telltale sign that its journey into an AI future has just begun. Focusing on three main strategic vectors:

✅ Accelerated computing

✅ AI full stack computing

✅ AI factories providing accessible computing infrastructure

Applications range from climate science, pharmaceutical research, physics, genetics… the list goes on. And which next iteration of Generative AI is waiting around the corner? It’s likely been trained and running on NVIDIA.

And Jensen's personal advice looking back over his career:

💡 Zero billion dollar market: Finding that niche market where you can be a gorilla

💡 "How hard can it be?": Keeping a can-do mindset

💡 99 failures, getting it right the 100th time = that's the moment you learn.

Food for thought.

Kudos go out to Alexander! NVIDIA's inception program is definitely worth exploring for the AI startup community.

Hope to see you all soon again!