Brett Adcock

The controller,

when it gets out of bounds of like what it's ever seen before.

Like you have carpet in here now and it's like really squishy.

The robot's doing fine, which is great.

But I think our old controller would not do well.

It's like, you have like really shaggy carpet here.

And it's like, yeah.

And so like, and it's like not very, it's like, you know, it's harder for a robot to walk around.

And so that was like, we had a really difficult time seeing that, even though it did well every day, seeing that scale to like lots of robots.

So we went back to the office, this is about a year and a half ago, and said, we need to basically refactor everything into a neural network.

And one of the big, and I think we just announced Helix two or three months ago now, I forget, like end of last year.

And it's basically entirely down the stack, including the controllers and neural net now.

There's like no code left really on the robot.

Maybe some code in certain pieces, but mostly just almost all of the thing is like a neural net at this point.

We removed the need for like almost over 100,000 lines of code when we launched Helix 2.

And so what you saw today was just like a robot that we can put now back into say the factory and these places that will run only on a neural net.

And I think we're running these robots right now, we're getting ready for deployment to customers and they're running incredibly well.

We have robots running like basically now in 24 seven shifts without stopping, without any faults for like days and days.

We just went like over, we just had like record time

this past week on the robot running until we saw, like, a false, like, almost, yeah, basically a whole week.