Sergey Levine

But I think if I had to summarize in one sentence

the big benefit that recent innovations in AI give to robotics is really the ability to leverage prior knowledge.

And I think the fact that the model is the same model, that's kind of always been the case in deep learning, but it's that ability to pull in that prior knowledge, that abstract knowledge that can come from many different sources.

That's really powerful.

What's up with that?

Yeah, yeah.

Yeah, so I have maybe two things I can say there.

I have some bad news and some good news.

So the bad news is what you're saying is really getting at the core of a long-running challenge with video and image generation models.

Yeah.

In some ways, the idea of getting intelligent systems by predicting video is even older than the idea of getting intelligent systems by predicting text.

But the text stuff turned into practically useful things earlier than the video stuff did.

I mean, the video stuff is great.

You can generate cool videos, and I think that the work there that's been done recently is amazing.

But it's not like just generating videos and images.

has already resulted in systems that have this kind of, like, deep understanding of the world where you can, like, ask them to, like, do stuff beyond just generating more images and videos.

Whereas with language, clearly it has.

And I think that this point about representations is really key to it.

One way we can think about it is this, that if you...

Imagine pointing a camera outside this building.