Lex Fridman

Almost all of them.

So you constantly have an eye on the entire stack and you're having intense discussions about the design of the entire stack.

So even if you're talking about a particular component, like cooling, networking, everybody's listening in.

Yeah, exactly.

And they can contribute, well, this doesn't work for the power distribution.

This doesn't work for the memory.

This doesn't work for this.

So as you mentioned, NVIDIA is this company that's adapting to the environment.

So which point can you say...

Did the environment change and you began adapting sort of secretly in the early days from GPU for gaming, maybe the early deep learning revolution to we're now going to start thinking of it as an AI factory.

What does NVIDIA do?

It produces AI, let's build a factory that makes AI.

So putting CUDA on GeForce could not afford to do.

Can you explain that decision?

Why boldly choose to do that anyway?

For people who don't know, it turned out to be, spoiler alert, one of the most incredibly brilliant decisions ever made by a company.

So CUDA turned out to be

an incredible foundation for computation in this AI infrastructure world.

Thank you.

You're just setting the context.