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

Sure. There's this idea called passive dynamics, which says that although you can use computers and actuators to make a motion, a mechanical system can make a motion just by itself if it gets stimulated the right way. Uh, so, uh, Tad McGeer in the, uh, I think in the mid eighties, uh, maybe it was in the late eighties starting to, started to work on that.

And he made this, uh, legged system that could walk down an inclined plane where the legs folded and unfolded and swung forward, you know, do the whole walk, walking motion where the only thing, there was no computer, uh, There were some adjustments to the mechanics so that there were dampers and springs in some places that helped the mechanical action happen.

It was essentially a mechanical computer. The interesting idea there is That it's not all about the brain dictating to the body what the body should do. The body is a participant in the motion.

I think that these days most robots aren't doing that. Most robots are... are basically using the computer to govern the motion. Now, the brain, though, is taking into account what the mechanical thing can do and how it's going to behave.

Otherwise, it would have to really forcefully move everything around all the time, which probably some solutions do, but I think you end up with a more efficient and more graceful thing if you're taking into account what the machine wants to do.

I like to talk about intelligence having two parts, an athletic part and a cognitive part. And I think Boston Dynamics, in my view, has sort of set the standard for what athletic intelligence can be. And it has to do with all the things we've been talking about, the The mechanical design, the real-time control, the energetics, and that kind of stuff.

But obviously, people have another kind of intelligence. And animals have another kind of intelligence. We can make a plan. Our meeting started at 9.30. I looked up on Google Maps how long it took to walk over here. It was 20 minutes. So I decided, okay, I'd leave my house at 9.00. which is what I did. You know, simple intelligence, but we use that kind of stuff all the time.

It's sort of what we think of as going on in our heads. And I think that's in short supply for robots. Most robots are pretty dumb. And as a result, it takes a lot of skilled people to program them to do everything they do. And it takes a long time. And if robots are gonna satisfy our dreams, they need to be smarter.

So the AI Institute is designed to combine that physicality of the athletic side with the cognitive side. So, for instance, we're trying to make robots that can watch a human do a task, understand what it's seeing, and then do the task itself. So sort of OJT, on-the-job training for robots, as a paradigm. Now, you know, that's pretty hard...

It's sort of science fiction, but our idea is to work on a longer timeframe and work on solving those kinds of problems. I have a whole list of things that are in that vein.

And using our hands, you know. Using your hands. The mechanics of interacting with all these things.

these two things you know you've never touched those things before right well i've touched ones like this okay look at all the things i can do right i can juggle and i'm rotating this way i can rotate it without looking i could fetch these things out of my pocket and figure out which one was which and all that kind of stuff yeah and uh i don't think we have much of a clue how all that works yet right and that's i really like putting that under the banner of athletic uh intelligence

I mean, one question you could ask, it isn't my question, but, you know, are they commercially viable? Will they increase productivity? And I think... You know, we're getting very close to that. I don't think we're quite there still. You know, most of the robotics companies, it's a struggle.

It's really the lack of the cognitive side that probably is the biggest barrier at the moment, even for the physically successful robots. But your question is, I mean, you can always do a thing that's more efficient, lighter, more reliable. I'd say reliability. I know that Spot, they've been working very hard on getting the the tail of the reliability curve up and they've made huge progress.

So the robots, you know, there's 1,500 of them out there now, many of them being used in practical applications day in and day out where, you know, where they have to work reliably. And, you know, it's very exciting that they've done that, but it takes a huge effort to get that kind of reliability in the robot. There's cost, too. You'd like to get the cost down.

Spots are still pretty expensive, and I don't think that they have to be, but it takes a different kind of activity to do that. Now that... I think that Boston Dynamics is owned primarily by Hyundai now, and I think that the skills of Hyundai in making cars can be brought to bear in making robots that are less expensive and more reliable and those kinds of things.

That's a good question. I think we're using the paradigm called stepping stones to moonshots. I don't believe, that was in my original proposal for the Institute, stepping stones to moonshots. I think if you go more than a year without seeing a tangible status report of where you are, which is the stepping stone, It could be a simplification.

You don't necessarily have to solve all the problems of your target goal, even though your target goal is going to take several years. Those stepping stone results give you feedback, give motivation, because usually there's some success in there. That's the mantra we've been working on. That's pretty much how I'd say Boston Dynamics has worked, where you make progress and show it as you go.

Show it to yourself, if not to the world.

Well, with Watch, Understand, Do, the project I mentioned before, we've broken that down into getting some progress with what is meaningfully watching something mean, breaking down an observation of a person doing something into the components, segmenting. You watch me do something. I'm going to pick up this thing and put it down here and stack this on it.

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