Marc Raibert

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243 appearances 1 recordings 1 series first heard Feb 2024 last heard Feb 2024

Marc Raibert’s voice in public audio — every appearance, attributed to the second.

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Lex Fridman Podcast · #412 – Marc Raibert: Boston Dynamics and the Future of Robotics · 16 Feb 2024 podcast

You mean convincing you it's okay that the dishwasher's broken?

Why is diligence important? Well, if you want a real robot solution, it can't be a very narrow solution that's going to break at the first variation in what the robot does or the environment if it wasn't exactly as you expected it. So how do you get there? I think having an approach that leaves you unsatisfied until you've embraced the bigger problem is the diligence I'm talking about.

Again, I'll point at Boss Dynamics. Some of the videos that we had showing the engineer making it hard for the robot to do its task. spot opening a door, and then the guy gets there and pushes on the door so it doesn't open the way it's supposed to, pulling on the rope that's attached to the robot so its navigation has been screwed up.

We have one where the robot's climbing stairs and an engineer is tugging on a rope that's pulling it back down the stairs. That's totally different than just the robot seeing the stairs, making a model, putting its feet carefully on each step. But that's what probably robotics needs to succeed, and having that broader

That broader idea that you want to come up with a robust solution is what I meant by diligence.

I learned something very early on with the first three-dimensional hopping machine. If you just show a video of it hopping It's a so what. If you show it falling over a couple of times and you can see how easily and fast it falls over, then you appreciate what the robot's doing when it's doing its thing.

So I think the reaction you just gave to the robot getting kind of interfered with or tested while it's going through the door, it's showing you the scope of the solution.

Well, I was the final edit for most of the videos up until until about three years ago or four years ago. And my theory of the video is no explanation. If they can't see it, then it's not the right thing. And if you do something worth showing, then let them see it. Don't interfere with a bunch of titles that slow you down or a bunch of distraction. Just do something worth showing and then show it.

That's brilliant. It's hard though for people to buy into that.

People have criticized, especially the big dog videos where there's a human driving the robot. And I understand the criticism now. At the time, we wanted to just show, look, this thing's using its legs to get up the hill. So we focused on showing that, which was, we thought, the story.

The fact that there was a human, so they were thinking about autonomy, whereas we were thinking about the mobility. And so, you know, we've adjusted to a lot of things that we see that people care about, trying to be honest. We've always tried to be honest.

I mean, it might be the most important ingredient, and that is robotics is hard. It's not gonna work right, right away. So don't be discouraged is all it really means. So usually when I talk about these things, I show videos and I show a long string of outtakes. And you have to have courage to be intrepid when you work so hard, you built your machine,

Then you're trying and it just doesn't do what you thought it would do, what you want it to do.

There's a video of Atlas climbing three big steps, and it's very dynamic, and it's really exciting, a real accomplishment. It took 109 tries, and we have video of every one of them. We shoot everything. Again, we, this is at Boston Dynamics. So it took 109 tries. But once it did it, it had a high percentage of success.

So it's not like we're cheating by just showing the best one, but we do show the evolved performance, not everything along the way. But everything along the way is informative, and it shows sort of there's stupid things that go wrong, like the robot just when you say go and it collapses right there on the start. That doesn't have to do with the steps.

Or the perception didn't work right, so you miss the target when you jump, or something breaks and there's oil flying everywhere. Yeah. But that's fun. Yeah.

Lots of control of evolution during that time. I think it took six weeks to get those 109 trials. Because there was programming going on. It was actually robot learning, but there were humans in the loop helping with the learning. So all data-driven.

It's remarkable. One of the accomplishments of Atlas is that the engineers have made a machine that's robust enough that it can take that kind of testing where it's falling and stuff, and it doesn't break every time. It still breaks. Part of the paradigm is to have people to repair stuff. You got to figure that in if you're going to do this kind of work.

I sometimes criticize the people who have their gold-plated thing and they keep it on the shelf and they're afraid to use it. I don't think you can make progress if you're working that way. You need to be ready to have it break and go in there and fix it. It's part of the thing. Plan your budget so you have spare parts and a crew and all that stuff.

I think it applies to everything anybody tries to do that's worth doing.

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