Andrej Karpathy

Each nine is constant.

Demos are encouraging.

Still a huge amount of work to do.

I do think it is a kind of a critical safety domain, unless you're doing vibe coding, which is all nice and fun and so on.

And so that's why I think this also enforced my timelines from that perspective.

Yeah, it's a much harder problem.

I mean, self-driving is just one of thousands of things that people do.

It's almost like a single vertical, I suppose.

Whereas when we're talking about general software engineering, it's even more, there's more surface area.

Yeah, basically, I'm not 100% sure if I fully agree with that.

I don't know how much we're getting for free, and I still think there's a lot of gaps in understanding in what we are getting.

I mean, we're definitely getting more generalizable intelligence in a single entity, whereas self-driving is a very special-purpose task that requires, in some sense, building a special-purpose task is maybe even harder in a certain sense because it doesn't fall out from a more general thing that you're doing at scale, if that makes sense.

So...

But I still think that the analogy doesn't, I still don't know if it fully resonates because like the LLMs are still pretty fallible and I still think that they have a lot of gaps and that it still needs to be filled in.

And I don't think that we're getting like magical generalization completely out of the box sort of in a certain sense.

And the other aspect that I want to also actually return to when I was in the beginning was self-driving cars are nowhere near done still.

Mm-hmm.

So even though, so the deployments still are pretty minimal, right?

So even Waymo and so on has very few cars, and they're doing that, roughly speaking, because they're not economical, right?

Because they've built something that lives in the future.