Jensen Huang

speaker

453 appearances 1 recordings 1 series first heard Jul 2026 last heard 27 Jul

Jensen Huang’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

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Y Combinator Startup Podcast · Jensen Huang: The Mindset That Built NVIDIA · 27 Jul 2026 podcast

How do you have all these autonomous systems, asynchronous systems working all the time?

And so what kind of design architecture makes perfect sense for that?

And so we have to go and go discover that.

And then, of course, the second thing is I want to use agents ourselves to make NVIDIA go faster.

And so we have Boris in the back, and we've got Cloud Code autonomously running in sandboxes all over NVIDIA, and that's really fantastic.

And some people use Codex, some people use Cloud Code, some people use Cursor, some people use Cognition.

And we let kind of a thousand flowers bloom, let people select the tools they want to use, and then we learn from all of that.

And so the second part is just helping the company move faster, use the tools.

And the more they use it, the more they'll learn about

how to make it work better in the future.

And the last part is discovering the future of solutions, technology for the future.

And maybe, you know, when we saw the early versions of Chain of Thought come out of Stanford, probably a decade ago at this point, maybe eight years ago, you know, the question is how effective is that going to be in reasoning and how scalable is it going to be

And what is the implication, for example, in computer vision if we can reason from prior knowledge?

And then the big breakthrough, of course, just in thinking through that small little domain, you come to realize that maybe we don't need as much data for cars to train a self-driving car, which led us to creating Alpamayo, which is the world's first thinking self-driving car.

And with just a million miles or so, a couple million miles, it's an incredibly great self-driving car.

And the reason for that is it's kind of like us, right?

We don't need that many miles before we could drive fairly well most of our lives.

And the reason for that is because we have prior knowledge from our language model

and we can decompose a situation we've never seen before and build it up out of things that we understood and know very well.

So that's an example of seeing something and then realizing the impact some time later.

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