Lex Fridman

As soon as you could specify, you could engineer it.

You've highly lauded Elon and XAI's accomplishment in Memphis in building Colossus supercomputer, probably in record time in just four months.

It's now at 200,000 GPUs and growing very quickly.

Is there something that you could speak to to understand about his approach that's instructive broadly to all the data center creators that's

that enable that kind of accomplishment?

His approach to engineering, his approach to the whole management of construction, everything.

Yeah.

I've been in a bunch of those meetings.

It's fun to watch because really not enough people ask the question like, okay, so, uh, can this be done a lot faster and how?

Why does it have to take this long?

And then that becomes an engineering question often.

And yes, I think when you get the ground truth of actually, I remember one of the times I was hanging out with him, he literally is going through the entire process of how to plug in cables into a rack.

He's working with an engineer on the ground that's doing that task, and he's just trying to understand what does that process look like so it can be less error-prone.

And just building up that intuition from every single task involved in putting together the data center, you start to immediately get a sense at the detailed scale and at the broad system scale of where the inefficiencies are.

And so you can make it more and more and more efficient.

Plus you have the big hammer of being able to say, let's do it totally different and remove all possible blockers.

Is there parallels in the NVIDIA Xtreme Systems co-design approach that you see in the way Elon approaches systems engineering?

In such incredibly complex systems that you're working with, is simplicity sometimes a good heuristic to reach for?

I mean, if I can just... I mean, the pod, the Vera Rubin pod that you announced is just incredible.

We're talking about seven chips, seven chip types, five purpose built rack types, 40 racks, 1.2 quadrillion transistors, nearly 20,000 NVIDIA DAIs,