Lex Fridman

Spell Q-U-O, a business phone platform for calling and messaging.

Basically, you have a bunch of people trying to help a larger group of people, and you want to orchestrate how they communicate with each other.

And this is just the system that does it extremely well, period.

Quo integrates AI into the whole shebang, organizing everything, generating summaries, highlighting the next steps, all that kind of stuff.

It just does it well.

The interface on top of the AI is also really strong.

So try Quo for free, plus get 20% off your first six months when you go to quo.com slash lex.

That's Q-U-O dot com slash lex.

This is the Lex Friedman Podcast.

And now, dear friends, here's Jensen Huang.

You've propelled NVIDIA into a new era in AI, moving beyond its focus on chip-scale design to now rack-scale design.

And I think it's fair to say that winning for NVIDIA for a long time used to be about building the best GPU possible.

And you still do.

But now you've expanded that to extreme co-design of GPU, CPU, memory, networking, storage, power, cooling, software.

the rack itself, the pod that you've announced, and even the data center.

So let's talk about extreme co-design.

What is the hardest part of co-designing a system with that many complex components and design variables?

I'm sure there's trade-offs there.

Plus, you have a complete disparate disciplines here.

I'm sure you have specialists in each one of these, high bandwidth memory.