BigDog

BigDog became LS3, which is the big load carrying one. Just a quick pause. It can carry 400 pounds.

Well, I was always a builder from a young age. I was lucky. My father was a frustrated engineer, and by that, I mean he wanted to be an aerospace engineer, but his mom from the old country thought that that would be like a grease monkey, and so she said no. So he became an accountant. But the result of that was our basement was always full of tools and equipment and electronics, and from a young age, I would watch him assembling an ICO kit or something like that. I still have a couple of his old ICO kits.

One of the things that underlies a lot of your work is that the robots you create, the systems you have created for over 40 years now have a kind of, they're not cautious. So a lot of robots that people know about move about this world very cautiously, carefully, very afraid of the world. A lot of the robots you built, especially in the early days, were very aggressive under actuated. They're hopping, they're wild, moving quickly. So is there a philosophy under underlying that? Well, let me tell you about how I got started on legs at all. When I was still a graduate student, I went to a conference. It was a biological legged locomotion conference, I think it was in Philadelphia. So it was all biomechanics people, researchers who would look at muscle and maybe neurons and things like that. They weren't so much computational people, but they were more biomechanics and maybe there were a thousand people there.

Right. What are some fond memories from the early days?

Is there a lot of technical challenges to go from hydraulic to electric? I had been in love with hydraulics and still love hydraulics. It's a great technology. It's too bad that somehow the world out there looks at it like it's old-fashioned or that it's icky. And it's true that you do. It is very hard to keep it from having some amount of dripping from time to time. But if you look at the performance, how strong you can get in a lightweight package, and of course we did a huge amount of innovation.

One of the things that stands out about the robots Boston Dynamics have created is how beautiful the movement is, how natural the walking is, and running is, even flipping is, throwing is. So maybe you can talk about what's involved in making it look natural. Well, I think having good hardware is part of the story and people who think you don't need to innovate hardware anymore are wrong, in my opinion. So I think one of the things, certainly in the early years for me, taking a dynamic approach where you think about what's the evolution of the motion of the thing going to be in the future and having a prediction of that that's used at the time that you're giving signals to it, as opposed to it all being sing, which is sing is sort of backward looking. It says, okay, where am I now? I'm going to try and adjust for that. But you really need to think about what's coming.

So at the leg lab, I believe most of the robots didn't have knees. How do you figure out what is the right number of actuators? What are the joints to have? What do you need to have? We humans have knees and all kinds of interesting stuff on the feet. The toe is an important part, I guess, for humans, or maybe it's not. I injured my toe recently and it made running very unpleasant. So that seems to be important. So how do you figure out for efficiency, for function, for aesthetics, how many joints to have, how many actuaries to have?

So this might be a good place to mention that you're now leading up the Boston Dynamics AI Institute newly formed, which is focused more on designing the robots of the future. I think one of the things, maybe you can tell me the big vision for what's going on, but one of the things is this idea that hardware still matters with organic design and so on. Maybe before that, can you zoom out and tell me what the vision is for the AI Institute? I like to talk about intelligence having two parts, an athletic part and a cognitive part.

I really like putting that under the banner of athletic intelligence. What are the big open problems in athletic intelligence? Boston Dynamics, with Spot, with Atlas, just have shown time and time again, pushed the limits of what we think is possible with robots. But where do we stand actually, if we zoom out. What are the big open problems on the athletic intelligence side? I mean, one question you could ask, that isn't my question, but are they commercially viable? Will they increase productivity? And I think we're getting very close to that. I don't think we're quite there still. 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.

If I can talk to you about teams, you've built an incredible team of Boston Dynamics, before at MIT and CMU, at Boston Dynamics, and now at the AI Institute. And you said that there's four components to a great team, technical fearlessness, diligence, intrepidness, and fun, technical fun. Can you explain each? Technical fearlessness, what do you mean by that? Sure. Technical fearlessness means being willing to take on a problem that you don't know how to solve, and study it, figure out an entry point, maybe a simplified version, or a simplified solution or something, learn from the stepping stone, and go back and eventually make a solution that meets your goals. I think that's really 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 Boston 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 idea that you want to come with a robust solution is what I meant by diligence.

Yeah. So, fun.

What to you is most beautiful about robotics? Sorry for the big romantic question. I think having the robots move in a way that's evocative of life is pretty exciting.

You mentioned about building teams and robotics teams and so on. How do you find great engineers? How do you hire great engineers? Well, it's a chicken and egg. If you have an environment where interesting engineering is going on, then engineers want to work there. And I think it took a long time to develop that at Boston Dynamics. In fact, when we started, although I had the experience of building things in the leg lab, both at CMU and at MIT, we weren't that sophisticated an engineering thing compared to what Boston Dynamics is now, but it was our ambition to do that. And Sarcos was another robot company, so I always thought of us as being this much on the computing side, and this much on the hardware side, and they were this. And then over the years, I think we achieved the same or better levels of engineering.

I really admire Elon as a technologist. I think that what he did with Tesla, it was just totally mind-boggling that he could go from this totally niche area that less than 1% of anybody seemed to be interested to making it, so that essentially every car company in the world is trying to do what he's done. So you got to give it to him. Then look at SpaceX, he's basically replaced NASA. That might be a little exaggeration, but not by much. So you got to admire the guy and I wouldn't count him out for anything. I don't think Optimus today is where Atlas is, for instance. I don't know, it's a little hard to compare them to the other companies. I visited Figure. I think they're doing well and they have a good team. I've visited Apptronik and I think they have a good team and they're doing well. But Elon has a lot of resources, he has a lot of ambition. I like to take some credit for his ambition. I think if I read between the lines, it's hard not to think that him seeing what Atlas is doing is a little bit of an inspiration. I hope so.

So as you work on the cognitive aspect of these robots, do you think we'll ever get to human level or superhuman level intelligence? There's been a lot of conversations about this recently, given the rapid development in large language models. I think that intelligence is a lot of different things and I think some things, computers are already smarter than people, and some things they're not even close. And I think you'd need a menu of detailed categories to come up with that. But I also think that the conversation that seems to be happening about AGI's puzzles me. So I ask you a question, do you think there's anybody smarter than you in the world?

So the Hawaiian shirt is almost a symbol of "why not?" Okay. What advice would you give to young folks that are trying to figure out what they want to do with their life? How to have a life they can be proud of? How they can have a career they can be proud of? When I was teaching at MIT, for a while, I had undergraduate advisees where people would have to meet with me once a semester or something and they frequently would ask what they should do. And I think the advice I used to give was something like, "Well, if you had no constraints on you, no resource constraints, no opportunity constraints and no skill constraints, what could you imagine doing?" And I said, "Well, start there and see how close you can get to what's realistic for how close you can get." The other version of that is try and figure out what you want to do and do that. A lot of people think that they're in a channel and there's only limited opportunities, but it's usually wider than they think.