Brett Adcock

This is like, let's go build really good human-owned hardware.

Let's make it cheap and really reliable.

Let's make sure it can do what humans can from a hardware perspective.

Meaning, you want to look at like a phone, where you can just add new apps to it, like the Do Laundry app, and the hardware doesn't need to change.

And the same exact hardware.

Like, humans don't need like new hardware to be able to go off and like learn how to do new skill now in the physical world.

So you want to build the humanoid hardware so it can do everything basically a human can, or as most of possible.

And then you want to go all in on neural networks, because you just can't code your way out of this problem.

And that was the first moment in 2023 where we're like, hot damn, this is going to really work.

This is going to be humanoid robots.

Hardware gets good, and then you're basically going to be, this is going to be a data play to train neural networks to run on humanoid hardware and do what humans do.

And then we launched figure two.

We did basically more work.

We started unveiling Helix, which is our neural network stack internally that we do here.

uh and uh now we've designed figure three which is our third generation robot you have here which is like it's the best human hardware in the world by far and we're now running robots that do like i watched it you know the other day uh unload dishes and fold laundry we had figure twos at bmw last year that worked six months every single day every uh

Every single day it worked.

A 10-hour shift every day for six months.

And we had, it was just, it was like the first time for us getting robots out to the real world, doing real stuff.

Like, you know, it's fun doing like, you know, demos at the office and showing it can really work.

But the real like level boss is like, how do we get robots out and do clients fire us?