Andrej Karpathy

And that is true, not just for the hardware pieces.

And also, let's not forget hardware, not just for a demo, but...

manufacturing of that hardware at scale.

It's like a whole different thing.

But for software as well, basically this robot currently thinks it's a car.

It thinks it's a car.

Some of the earlier demos, actually, we were talking about potentially doing them outside in the parking lot because that's where all of the computer vision was working out of the box instead of inside.

But all the operating system, everything just copy-pastes.

Computer vision, mostly copy-pastes.

I mean, you have to retrain the neural nets, but the approach and everything and data engine and offline trackers and the way we go about the occupancy tracker and so on, everything copy-pastes.

You just need to retrain the neural nets.

And then the planning control, of course, has to change quite a bit.

But there's a ton of copy-paste from what's happening at Tesla.

And so if you were to go with the goal of like, okay, let's build a million human robots and you're not Tesla, that's a lot to ask.

If you're Tesla, it's actually like...

It's not that crazy.

I think it's going to take a long time, but the way you want to structure the development is you need to say, okay, it's going to take a long time.

How can I set up the product development roadmap so that I'm making revenue along the way?

I'm not setting myself up for a zero-one loss function where it doesn't work until it works.

You don't want to be in that position.