Lex Fridman

But it's not just inside the company.

You're shaping the landscape, the broader global landscape of innovation.

Like putting those ideas out there, you really are manifesting reality.

Yeah.

So one of the things you've been a believer for a long time is scaling laws broadly defined.

So are you still a believer in the scaling laws?

Yeah, we have more scaling laws now.

So I think you've outlined four of them with pre-training, post-training, test time, and agentic scaling.

What do you think, when you think about the future, deep future and the near-term future, what are the blockers?

that you're most concerned about that keep you up at night, that you have to overcome in order to keep scaling?

But there's a tricky thing there that you have to anticipate and predict, which is some of these components, it requires different kind of hardware to really do it optimally.

So you have to anticipate where the AI innovation is going to lead.

For example, make sure you're experts with sparsity.

Perfect.

With hardware, you can't just pivot on a week's notice.

You have to anticipate what that's going to look like.

So good.

That's so scary and difficult to do, right?

So you're listening to the whispers across the industry, the ad-libs.

Obviously, the design of the system