Andrej Karpathy

So, but it's, it definitely feels tractable and it feels like at least the team at Tesla, which is what I saw internally is definitely on track to that.

Yeah, expert intuition.

Yeah, I would say definitely like to use a game analogy, there's some fog of war, but you definitely also see the frontier of improvement and you can measure historically how much you've made progress.

And I think, for example, at least what I've seen in roughly five years at Tesla, when I joined, it barely kept lane on the highway.

I think going up from Palo Alto to SF was like three or four interventions.

Anytime the road would do anything geometrically or turn too much, it would just like not work.

And so going from that to a pretty competent system in five years and seeing what happens also under the hood and what the scale at which the team is operating now with respect to data and compute and everything else is just massive progress.

You're making progress, and you see what the next directions are, and you're looking at some of the remaining challenges, and they're not perturbing you, and they're not changing your philosophy, and you're not contorting yourself.

You're like, actually, these are the things that we still need to do.

Basically, as I described, I think over time, during those five years, I've gotten myself into a bit of a managerial position.

Most of my days were meetings and growing the organization and making high-level strategic decisions about the team and what it should be working on and so on.

It's kind of like a corporate executive role.

And I can do it.

I think I'm okay at it.

But it's not fundamentally what I enjoy.

And so I think when I joined, there was no computer vision team because Tesla was just going from the transition of using Mobileye, a third-party vendor for all of its computer vision, to having to build its computer vision system.

So when I showed up, there were two people training deep neural networks.

And they were training them at a computer at their legs.

Yeah, and so...

I kind of grew that into what I think is a fairly respectable deep learning team, a massive compute cluster, a very good data annotation organization.