Sergey Levine

Yeah.

So physical intelligence aims to build robotic foundation models.

And that basically means general purpose models that could, in principle, control any robot to perform any task.

We care about this because we see this as a very fundamental aspect of the AI problem.

Like the robot is essentially encompassing all AI technology.

So if you can get a robot that's truly general, then you can do hopefully a large chunk of what people can do.

And where we're at right now is I think we've kind of gotten to the point where we've built out a lot of the basics.

And, you know, I think those basics actually are pretty cool.

Like they work pretty well.

We can get a robot that will like fold laundry and that will go into a new home and like try to clean up the kitchen.

But in my mind, what we're doing at Physical Intelligence right now is really the very, very early beginning.

It's just like putting in place the basic building blocks on top of which we can then tackle all these like really tough problems.

So there are a few things that we need to get right.

I mean, dexterity obviously is one of them.

And in the beginning, we really wanted to make sure that

we understand whether the methods that we're developing have the ability to tackle like the kind of intricate tasks that people can do.

As you mentioned, like folding a box, folding different articles of laundry, cleaning up a table, making a coffee, that sort of thing.

And that's like, that's good.

Like that works.

I think that the results we've been able to show are pretty cool.