#412 – Marc Raibert: Boston Dynamics and the Future of Robotics

27:44And then there's a third part to keep the body at an attitude that's upright. Because if it gets too far, you could hop and just keep rotating around. But if motion of the joints at the hips, so you have to do that. And we did that by applying a torque between the legs and the body every time the foot's on the ground. You only can do it while the foot's on the ground in the air. You know, the physics don't work out. How far does it have to tell before it's too late to be able to balance itself or it's impossible to balance itself, correct itself? Well, you're asking a just in question because in those days, we didn't actually optimize things and they probably could have gone much further than we did and then had higher performance and we just kind of got you know a sketch of a solution and worked on that and then in years since some people working for us some people working for others people came up with all kinds of equations for or you know algorithms for how to do a better job be able to go faster one of my students worked on getting things to go faster another one worked on climbing over obstacles because when you're running, it's one on the open ground, it's one thing.

28:58If you're running up a stair, you have to adjust where you are, otherwise things don't work out right. You land your foot on the edge of the step. So there's other degrees of freedom to control if you're getting to more realistic practical situations. I think it's really interesting to ask about the early days because believing in yourself, believing that there's something interesting here, and then you mentioned finding somebody else, Ben Brown. What's that like finding other people with whom you can Build this crazy idea and actually make it work probably the smartest thing I ever did just to find the other people I mean when I look at it now, you know, I look at Boston Dynamics and all the really excellent engineering there You know people who really make stuff work You know, I'm I'm only the the dreamer So we talk about Pogo stick robot or legged robots, whether it's quadrupeds or humanoid robots, did people doubt that this is possible?

29:55Did you experience a lot of people around you kind of? I don't know if they doubted whether it was possible, but I think they thought it was a waste of time. Oh, it's not even an interesting problem. I think for a lot of people, you know, people who were, I think it's been both though. Some people, I think, I felt like they were saying, oh, you know, why are you wasting your time on this stupid problem? And then, but then I've been at many things where people have told me it's been an inspiration to go out and, you know, attack these harder things. And I think it has turned out, I think, like, a locomotion has turned out to be a useful thing.

30:34Did you ever have, like, doubt about bringing atlas to life, for example, or with big dog just every step of the way? Did you have doubt, like, what would this is too hard of a problem? I mean, at first I wasn't an enthusiast for the humanoids, because again, it goes back to saying, what's the functionality? And the form wasn't as important as the functionality. And also, you know, there's an aspect to humanoid robots that's about all about the cosmetics, where there isn't really other functionality. And that kind of is off -punning for me as a roboticist. I think the functionality really matters.

31:14So, probably that's why I avoided human robots, humanoid robots to start with. But I'll tell you, after we start working on them, you could see that the connection and the impact with other people, whether they're lay people or even other technical people, there's a special thing that goes on. Even though most of the humanoid robots aren't that much like a person. But we have to put more fives and we see that's for humanity But also like with the with spot you can see Not the humanity, but the whatever we find compelling about social interactions there in spot as well I'll tell you know I go around giving talks and take spot to a lot of them and it's amazing The media likes to say that they're terrifying and and that people are afraid and And YouTube commenters like to say that it's frightening, but when you take a spot out there Now, maybe it's self -selecting, but you get a crowd of people who want to take pictures, want to pose for selfies, want to operate the robot, want to pet it, want to put clothes on it.

32:19It's amazing. Yeah, love spot. So if we move around history a little bit, so you said, I think in the early days of Boston Dynamics that you quietly worked on making a running version of I -Bone. Sony's robot dog. Yeah. It's just an interesting little tidbit of history for me. What stands out to you in memory from that task? For people who don't know that little dog robot moves slowly. How did that become big dog? What was involved there? What was the dance between how do we make this cute little dog versus a thing that can actually care a lot of payload and move fast and stuff like that? What the connection was is that at that point, Boston Dynamics was mostly a physics -based simulation company.

33:04So when I left MIT to start Boston Dynamics, There was a few years of overlap, but the concept wasn't to start a robot company. The concept was to use this dynamic simulation tool that we developed to do robotics for other things. But working with Sony, we got back into robotics by doing the Ibo runner, we made some tools for programming Curio, which was a small, a humanoid, this big that could do some dancing and other kinds of fun stuff. And I don't think it ever reached the market even though they did show it. You know, when I look back, I say that we got us back where we belonged. Yeah. You rediscovered the soul of the company.

33:46That's right. And so from there, it was always about robots. Yeah. So you started Boston Dynamics in 1992. Right. What are some fond memories from the early days? One of the robots that we built wasn't actually a robot. It was a surgical simulator, but it had forced feedback. So it had all the techniques of robotics. You looked down into this mirror it actually was, and it looked like you were looking down onto the body you were working on. Your hands were underneath the mirror, so there were where you were looking. You had tools in your hands that were connected up to these forced feedback devices made by another MIT spin -out sensible technologies.

34:32So they made the first feedback device. We attached the tools and we brought all the software and did all the graphics. So we had 3D computer graphics. It was in the old days when this was in the late 90s when you had the silicon graphics computer that was about this big. You know, it was the heater in the office basically. And we were doing surgical operations. I nastimosis, which was stitching tubes together, you know, tubes like blood vessels or other things in their body. And you could feel and you could see the tissues move and it was really exciting. And the idea was to make a trainer to teach surgeons how to do stuff.

35:11We built a scoring system because we interviewed surgeons that told us, you know, what you're supposed to do and what you're not supposed to do. You're not supposed to tear the tissue, you're not supposed to touch it in any place, except for where you're trying to engage. There were a bunch of rules. So we built this thing and took it to a trade show, a surgical trade show. And the surgeons were practically lined up. Well, we kept the score and we posted their scores like on a video game. And those guys are so competitive that they really, really loved doing it. And they would come around and they see someone's score was higher there, so they would come back.

35:46But we figured out shortly after that we thought surgeons were going to pay us to get trained on these things. And the surgeons thought we should pay them in order to so they could teach us about the thing. And there was no money from the surgeons. And we looked at it and thought, well, maybe we could sell it to hospitals that would teach to train their surgeons. And then we said, well, we're this at the time we were probably a 12 person company or maybe 15 people. I don't remember. There's no way we could go after a marketing activity. The company was all bootstrapped in those years. We never had investors until Google bought us, which was after 20 years.

36:24So we didn't have any resources to go after hospitals. So we, at one day, Rob and I were looking at that, and we said, we'd built another simulator for knee arthroscopy, and we said, this isn't going to work. and we killed it and we moved on and that was really a milestone in the company because we you know we sort of understood who we were and what would work and what wouldn't even though technically it was really a fascinating thing. What was that meaning like were you just like sitting at it? You know what? Probably we're going to pivot completely. We're going to let go of this thing we put so much hard work into and then go back to the thing.

37:07It just always felt right when we did it, you know. Just look at each other and say, let's build robots. Yeah. What was the first robot we built under the flag of Boston dynamics? Big dog? Well, there was the Ibo runner, but it wasn't even a whole robot. It was just legs that we took off the legs on Ibo's and attached legs we'd made. And you know, we got that working and showed it to Sony people. We worked pretty closely with Sony in those years. One of the interesting things is that it was before the internet and zoom and anything like that. So we had six ISDN lines installed and we would have a telecon every week that worked at very low frame rate, something like 10 hertz.

37:54You know, English across the boundary with Japan was a challenge, trying to understand what each of us was saying and have meetings every week for several years doing that. And it was a pleasure working with them. They were really supporters. They seemed to like us and what we were doing. That was the real transition from us being a simulation company into being a robotics company again. It was a quadrupet. The legs were four legs or two legs. Yeah, no four legs. Yeah, and what did you learn from that experience of building it basically a fast moving quadruped? Mostly we learned that something that small doesn't look very exciting when it's running.

38:37It's like it's scampering and you had to watch a slowmo for it to look like it was interesting. If you watch it fast it was just like a that's funny. One of my things was to show stuff in video from the very early days of the hopping machines. And so I was always focused on how it's going to look through the viewfinder. Running iBot didn't look so cool through the viewfinder. So what came next in terms of what was a big next milestone in terms of the robot you built? I mean you got to say that Big Dog was sort of put us on the map and got our heads really pulled together. We scaled up the company.

39:16The big dog was the result of Alan Rudolph at DARPA starting a biodynamics program. He put out a request for proposals. I think there were 42 proposals written and three got funded. One was Big Dog, one was a climbing robot rise, and that put things in motion. We hired Martin Bueller. He was a professor at Montreal at McGill. He was incredibly important for getting big dog out of the lab and into the mud, which is a key step to really be willing to go out there and build it, break it, fix it, which is sort of one of our models at the company. So testing it in the real world. For people who don't know big dog, maybe you can correct me, but it's a big quadruped four leg robot that it looks big, probably carry a lot of weight.

40:12not the most weight that Boston and Amsterdam have built, but a lot. Well, it's the first thing that we're... So, let's see, if we go back to the leg lab, we'd built a quadruped that could do many of the things that Big Dog did, but it had a hydraulic pump sitting in the room with hoses connected to the robot. It had a Vax computer in the next room, it needed its own room, because it was this giant thing with air conditioning, and it had this very complicated bus connected to the robot. And the robot itself just had the actuators, it had gyroscopes for sensing and other, some other sensors, but all the power and computing was offboard.

40:50BigDog had all that stuff integrated on the platform. It had a gasoline engine for power, which was a very complicated thing to undertake. It had to convert the rotation of the engine into hydraulic power, which is how we actuated it. So there was a lot of learning just on the building the physical robot and the system integration for that. And then there was the controls of it. So for Big Dog, we brought it all together onto one platform and then so you could take it out in the woods. Yeah, and you did. We did. We spent a lot of time down at the Marine Corps base in Aquanico where there was a trail called the Guadalcanal Trail.

41:34And our milestone that DARPA had specified was that we could go on this one particular trail that involved a lot of challenge. And we spent a lot of time, our team, spent a lot of time down there. Those were fun days. Hiking with the robot. So what did you learn about what it takes to balance the robot like that on a trail on a hiking trail? on the woods, but basically forget the woods, just the real world. That's the big leap into testing in the real world. As challenging as the woods were, working inside of a home or in an office is really harder. Because when you're in the woods, you can actually take any path up the hill.

42:18All you have to do is avoid the obstacles. There's no such thing is damaging the woods, at least, you know, to first order. Whereas if you're in a house, you can't leave scuff marks, you can't bang into the walls, the robots aren't very comfortable bumping into the walls especially in the early days. So I think those were actually bigger challenges once we faced them. It was mostly, you know, getting the systems to work well enough to gather the hardware systems to work. And the controls. In those days, we did have a human operator who did all the visual perception going up the Guadalcanal Trail.

42:53So, there was an operator who was right there who was very skilled at even though the robot was balancing itself and placing its own feet if the operator didn't do the right thing. It wouldn't go. But years later, we went back with one of the electric precursor to spot and we had advanced the controls and everything so much that an amateur, complete amateur could operate the robot the first time up and down and up and down whereas it's taken us years to get there in the previous robot. So if you fast forward, big dog eventually became spot. So big dog became LS3 which is the big load carrying one.

43:31Just just a quick pause, it can carry 400 pounds. It was designed to carry 400 but we had it carrying about a thousand pounds. Of course you did. We had one carrying the other one. We had two of them. We had one carrying the other one. There's a little clip of that. We should put that out somewhere. That's from like 20 years ago. Wow. Wow. It can go for very long distances. You can travel 20 miles. Yeah. Gasoline. Gasoline. Yeah. That adventure says, okay, sorry. So LS3, then how did that lead to spot? But so BigDog and LS3 had engine power and hydraulic actuation. Then we made a robot that was electric power.

44:21So there's a battery driving a motor driving a pump, but still hydraulic actuation. Larry sort of asked us, could you make something that weighed 60 pounds that would not be so intimidating if you had it in a house where there were people. And that was the inspiration behind the spot. Pretty much as it exists today, we did a prototype the same size that was the first all -electric non -hydraulic robot. What was the conversational Larry Page like about? So here's a guy that is very product focused and can see a vision for what the future holds. That's just interesting kind of aside, What was the brainstorm about the future of bodies with him like?

45:03I mean it was almost as simple as when I just said he you know we have a small meeting he said yeah jeez you know do you think you could make a smaller one that wouldn't be so intimidating like a big dog yeah if it was in your house and I said yeah we could do that and we started and did is there a lot of technical challenges to go from hydraulic to electric you know 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.

45:47But 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 most of hydraulic Control that is the valve that controls the flow of oil had been designed in the fifties for airplanes It had been made robust enough safe enough that you could count on it so that humans could fly in airplanes and Very little innovation had happened, you know that might not be fair to the people who make the valves I'm sure that they did innovate. But the basic design had stayed the same. And there was so much more you could do. And so our engineers designed valves, the ones that are in Atlas, for instance, that had new kinds of circuits.

46:33They sort of did some of the computing that could get you much more efficient use. They were much smaller in lighter so the whole robot could be smaller in lighter. We made a hydraulic power supply that had a bunch of components integrated in this tiny package. It's about this big. The size of a football weighs 5 kilograms and it produces 5 kilowatts of power. Of course, it has that battery operating, but it's got a motor, a pump, filters, heat exchanger to keep it cool, some valves, all in this tiny little package. So hydraulics, could still have a ways to go. Well, one of the things that stands out about the robots, the boss of the name is the creator, this is how beautiful the movement is.

47:18How 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 servoing, which is servoing is sort of backward looking.

48:02It 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 how far ahead do you have to look in time? It's interesting. I think that the number is only a couple of seconds for spot. So there's a limited horizon type approach where you're recalculating, assuming what's going to happen in the next second or second and a half. And then you keep iterating, you know, the next, even though a tenth of a second later, you'll say, okay, let's do that again and see what's happening. And you're looking at what the obstacles are where the feet are going to be placed.

48:38How to, you know, you have to coordinate a lot of things if you have obstacles and you're balancing at the same time. And it's that limited horizon type calculation that's doing a lot of that. But if you're doing something like a summer song, you're looking out a lot further, right? If you want to stick to landing, you have to get the, you have to, at the time of launch, have momentum and rotation, all those things coordinated so that a landing is within reach. How hard is it to stick a landing? I mean, it's very much under -exuated. Like, once you've in the air, you don't have as much control about anything.

49:19So how hard is it to get that to work? First of all, it did flips with a hopping robot. If you look at the first time we ever made a robot do a summer solve, it was in a planar robot. You know, it had a boom. So it could only, it was restricted to the surface of a sphere, we call that planar. So it could move for an aft, it could go up and down and it could rotate. And so the calculation of what you need to do to get a, to stick a landing isn't all that complicated. You have to look at, you know, you have to get time to make the rotation. So how hard you jump, how high you jump gives you time.

49:55You look at how quickly you can rotate. And so, you know, if you get those two right, then when you land, do you have the feet in the right place? And you have to get rid of all that rotational and linear momentum. But you know, that's not too hard to figure out. And we made, you know, back in about 1985 or six, I can't remember. We had a simple robot doing summer solts. To do it in 3D, really the calculations is same. You just have to be balancing in the other degrees of freedom. If you're just doing a summer salt, it's just a plain or thing. Roy and Maraba is my graduate student and we ran MIT, which is when we made a two -legged robot do a 3D summer salt for the first time.

50:36There, in order to get enough rotation rate, you needed to do tucking also. We'd draw the legs in order to accelerate it. And he did some really fascinating work on how you stabilize more complicated maneuvers. Remember, he was a gymnast, a champion gymnast before he'd come to me. So he had the physical abilities. And he was an engineer, so he could translate some of that into the math and the algorithms that you need to do that. He knew how humans do it. He just had to get robots to do the same. Unfortunately though, humans don't really know how they do it. Yeah, right. We were coached. We we have ways of learning, but do we really understand in the physical in a physics way?

51:21Uh, what we're doing? Probably most gymnasts and athletes don't know. So in some way by building robots, you are in part understanding how humans do like walking. Most of us walk without considering how we walk really, right? And how we make it so natural and efficient, all those kinds of atlas. Still doesn't walk like a person and it still doesn't walk quite as gracefully as a person, even though it's been getting closer and closer. The running might be close to a human, but the walking is still a challenge. That's interesting, right? That running is closer to a human. It just shows that the more aggressive and kind of the more you leap into the unknown, the more natural it is.

52:03I mean, walking is kind of falling always, right? And something weird about the knee that you can kind of do this folding and unfolding and get it to work out just a human can get it to work out just right There's compliance is compliance main springiness in the design that are important to know what works Well, we used to have a motto at boss dynamics in the early days, which was the half the run before you can walk That's a good motto because you also had Wildcat which was one of the, along the way towards spot, which is a quadruped to 19 miles an hour on flat terrain. Is that the fastest you've ever built?

52:42Oh yeah, might be the fastest quadruped in the world. I don't know. For a quadruped probably, of course it was probably the loudest too. So we had this little racing go -kart engine on it. And we would get people from three buildings away sending us complaining about how loud it was. So at the leg lab, I believe most of the robots didn't have knees. What's the, how do you figure out what is the right number of actuators? What are the joints to have? What do you need to have? You know, we humans have knees and all kinds of interesting stuff on the feet. The toe is an important part, I guess, for humans.

53:22Or maybe it's not. I injured my toe recently and it made running very unpleasant. So that seems to be kind of important. So how do you figure out for efficiency, for function, for aesthetics, how many joints to have, how many actions to have? Well, it's always a balance between wanting to get where you really want to get and what's practical to do based on your resources or what you know and all that. So, I mean, the whole idea of the Pogostick was to do simplification. obviously it didn't look like a human. I think a technical scientist could appreciate that we were capturing some of the things that are important in human locomotion without it looking like it without having a knee and ankle.

54:08I'll tell you the first sketch that Ben Brown made when we were talking about building this thing was a very complicated thing with Zillions of Springs. Lots of It looked like much more like a kangaroo or an ostrich or something like that. Things we were paying a lot of attention to at the time. So my job was to say, okay, well, let's do something simpler to get started, and maybe we'll get there at some point. I just love the idea that you two were studying kangaroos and ostriches. Oh yeah, we did, we filmed and digitized data from horses. I did a dissection of an ostrich at one point, which has absolutely remarkable legs.

54:56Dom question, does she have a lot of musculature on the legs or no? Most of it's up in the feathers, but there's a huge amount going on in the feathers, including a knee joint, the knee joint's way up there. The thing that's halfway down the leg that looks like a backwards knee is actually the ankle. The thing on the ground which looks like the foot is actually the toes, it's an extended toe. But the basic morphology is the same in all these animals. What do you think is the most beautiful movement of an animal? What animal do you think is the coolest land animal? Let's go because fish is pretty cool like the fish was the water, but like a leg it look emotion You know the slow mobs of cheetahs running are are incredible, you know there they there's so much back motion and You know grace and of course they're moving very fast The animals running away from the cheetah are pretty exciting, you know the pronghorn Which you know they they do this all four legs at once jump called the proc to kind of confuse the, especially if there's a group of them to confuse whoever's chasing them.

56:07So, did you like a misdirection type of thing? Yep, they do a misdirection thing. The front -on views of the cheetahs running fast where the tail is whipping around to help in the turns to help us stabilize in the turns, that's pretty exciting. Because they spent a lot of time in the air, I guess, that they're running that fast. But they also turn very fast. Is that a tail thing or do you have to have contact with the ground? Everything in the body is probably helping turn. because they're chasing something that's trying to get away. That's also zigzagging around. But I would be remiss if I didn't say, humans are pretty good to watch gymnasts, especially these days.

56:44They're doing just incredible stuff. Well, like especially like Olympic level gymnasts. See, but there could be, there could be cheetahs there are Olympic low. We might be watching the average cheetah versus like that could be like a really special cheetah that can do like, you're right. When did the knees first come into play in you building legged robot? I in big dog. Big dog. Yeah, big dog came first and then little dog was later. And you know, there was a big compromise there. Human knees have multiple muscles and you could argue that there's, I mean, it's a technical thing about negative work when you're contracting a joint, but you're pushing, out that's negative work.

57:32And if you don't have a place to store that, it can be very expensive to do negative work. And most of, and in Big Dog there was no place to store negative work in the knees. But Big Dog also had pogos -dick springs down below. So part of the action was to comply in a bouncing motion. You know, later on in spot, we took that out and as we got further and further away from the leg lab we had more energy -driven controls. Is there something to be said about like knees that go forward versus backward? Sure. There's this idea called passive dynamics which says that although you can use computers and actuators to make a motion.

58:19A mechanical system can make a motion just by itself if it gets stimulated the right way. So, Tad McGear in the, I think in the mid -80s, maybe within the late 80s, started to work on that. And he made this legged system that could walk down and then climb plain where the legs folded and unfolded and swung forward. You know, do the whole walking motion where where there was no computer. 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.

59:07The body is a participant in the motion. So a great design for a robot has a mechanical component where the movement is efficient even without a brain. Yes. How do you design that? I think that these days most robots aren't doing that. Most robots are basically using the computer to to govern the motion. Now the 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.

59:51So 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 the future. I think one of the things, maybe you can tell me the big vision for what's going on. 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? you know, I like to talk about intelligence having two parts, an athletic part and a cognitive part. And I think, you know, Boston Dynamics, in my view, has sort of set the standard for what athletic intelligence can be.

1:00:40And you know, it has to do with all the things we've been talking about, 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 of 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 nine, which is what I did. 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.

1:01:21Most 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 going to, you know, 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 for robots, on the job training for robots, as a paradigm. Now that's pretty hard and it's sort of science fiction, but our idea is to work on a longer time frame and work on solving those kinds of problems.

1:02:16And I have a whole list of things that are kind of like in that in that vein. Maybe we can just take many of the things you mentioned and just take it as a tangent. Okay. First of all, athletic intelligence is a super cool term. And that really is intelligence. We humans kind of take it for granted that we're so good at walking and moving about the world. And using our hands, you know, the mechanics of interacting with all these two things, you know. I'm not, I'm not looking for it. Well, I've touched ones like this. Look at all the things I can do, right? I can juggling, I'm rotating this way.

1:02:51I can rotate it without looking. I could fetch these things out of my pocket and figure out which one was switched and all that kind of stuff. And 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 intelligence. What are the big open problems in athletic intelligence? So Boston Dynamics, with Spot, with Atlas, just have shown time and time again, like push the limits of what we think is possible with robots. But where do we stand actually, if we kind of zoom out? What are the big open problems on the athletic intelligence side?

1:03:30I mean, one question you could ask that isn't my question, but, you know, are they commercially viable? Could, will they increase productivity? And I think, you know, we're getting very close to 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. But your question is, I mean, you can always do a thing that's more efficient, lighter, more reliable. I'd say reliability. You know, I know that spot they've been working very hard on getting the tail of the reliability curve up and they've made a huge progress.

1:04:14So the robots, you know, there's a 1 ,500 of them out there now. Many of them being used in practical applications day in and day out 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 costs 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, you know, I think, you know, that Boston Dynamics is owned primarily by a 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.

1:05:08So on the Cognizide for the I institute, what's the trade -off between moonshot projects for you and maybe incremental progress? 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 my chest. I think if you go more than a year without seeing a tangible status report of where you are, which is the stepping stone, and it could be a simplification, right? 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.

1:05:49You know, those stepping stone results give you feedback, give motivation because usually there's some success in there, and so you know, That's the mantra we've been working on. And 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. What does success look like? What are some of the milestones you're chasing? Well, we've watched, 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.

1:06:39Segmenting, you watch me do something. I'm going to pick up this thing and put it down here and stack this on it. Well, it's not obvious if you just look at the raw data, what the sequence of acts are. It's really a creative intelligent act for you to break that down into the pieces and understand them in a way. So you could say, okay, what skill do I need to accomplish each of those things? So we're working on you know the front end of that kind of a problem where we observe and translate the if it may be video it may be live into a Description of what we think is going on and then trying to map that into skills to accomplish that and may have been developing skills as well So you know, we have kind of multiple stabs at the pieces of doing that and this is usually video of humans manipulating objects with their hands kind of thing.

1:07:29We're starting out with bicycle repair, some simple bicycle repair. Oh, no. That seems complicated. That seems really complicated. Well, it is, but there's some parts of it that aren't like putting the seat in, you know, into the, you know, you have a tube that goes inside of another tube and there's a latch, you know, that should be within range. Is it possible to observe, to watch a video like this without having explicit model of what a bicycle looks like. I think it is. And I think that's the kind of thing that people don't recognize. Let me translate it to navigation. I think the basic paradigm for navigating a space is to get some kind of sensor that tells you where an obstacle is and what's open, build a map, and then go through the space.

1:08:14But if we were doing on the job training where I was giving you a task, I wouldn't have to say anything about the room. We came in here. All we did is adjust the chair, but we didn't say anything about the room and you know, we could navigate it. So I think there's opportunities to build that kind of navigation skill into robots, and we're hoping to be able to do that. So operate successfully under a lot of uncertainty. Yeah, and lack of specification. Lack of specification. I mean, that's what sort of intelligence is, right? Kind of dealing with understanding a situation even though it wasn't explained.

1:08:50So how big of a role does machine learning play in all of this? Is this more and more learning -based? You know, since Chat GBT, which is a year ago, basically, there's a huge interest in that and a huge optimism about it. And I think that there's a lot of things that machine learning, that kind of machine learning. Now, Chris, there's lots of different kinds of machine learning. I think there's a lot of interest in optimism about it. I think the facts on the ground are that doing physical things with physical robots is a little bit different than language. The tokens don't exist. Pixel values aren't like words, but I think that there's a lot that can be done there.

1:09:40We have several people working on machine learning approaches. I don't know if you know, but we opened an office in Zurich recently. Marco Hutter, who's one of the real leaders in reinforcement learning for robots, is the director of that office. He's still half -time at ETH, the university there, where he has an unbelievably fantastic lab. and then he's half time leading, will be leading off efforts in the zero -goffice. So we have a healthy learning component, but there's part of me that still says if you look out in the world at what the most impressive performances are, there's still pretty much, I hate to use the word traditional, but that's what everybody's calling it, traditional controls, like model predictive control.

1:10:33The thing, the Atlas performances that you've seen are mostly model predictive control. They've started to do some learning stuff that's really incredible. I don't know if it's all been shown yet, but you'll see it over time. And then Marco has done some great stuff and others. So especially for the athletic intelligent piece, the traditional approach seems to be the one that still performs the best. I think we're going to find a mating in the tube and we'll have the best of both worlds. And we're working on that at the Institute too. If I can talk to you about teams, you've built an incredible team of boss dynamics before it on my TNC view, and boss dynamics and out the AI Institute.

1:11:13You said that there's four components to a great team. Technical fearlessness, diligence, and trepidness 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. And I think that's really important. The fearlessness comes into play because some of it has never been done before.

1:12:00Yeah, and you don't know how to do it and you know just easier stuff to do in life So, you know, I mean I don't know watch understand do it's a it's a mountain of a of a challenge So that's the really big challenge you're you're tackling now can we watch humans at scale and have robots by watching humans become effective Actors in the world. Yeah, I mean we have others like that. I we have one called inspect diagnosed fix like, you know, you call up the Maytag repairman. Okay, he's the one who you don't have to call, but you know, you call up the dishwasher repair person and they come to your house and they look at your machine.

1:12:44It's already been actually figured out that something doesn't work, but they have that kind of examine it and figure out what's wrong and then fix it. And I think robots should be able to do that. We already, Boston Dynamics already has spot robots collecting data on machines, things like thermal data, reading the gauges, listening to them, getting sounds. And that data are used to determine whether they're healthy or not. But the interpretation isn't done by the robots yet. And certainly the fixing, the diagnosing and the fixing isn't done yet. But I think it could be. And yeah, that's bringing the AI and combining it with the physical skills to do it.

1:13:28Yeah, and you're referring to the fixing in the physical world. I can't wait until you can fix the psychological problems of humans and show up and talk, do therapy. Yeah, that's a different thing. Yeah, it's different. Well, but let's all part of the same thing again, humanity. Maybe, maybe you mean convincing you it's okay that the dishwasher is broken just to the Yeah, the marketing approach. Yeah, exactly. It's all, yeah, don't, don't sweat the small stuff. Yeah, it's supposed to fix the dishwasher. It'll convince you that it's okay that the dishwasher is broken. It's a different approach.

1:14:06Dilligence. 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 is the diligence I'm talking about. And again, I'll point it out as dynamics. I think they've done 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.

1:14:58We have one where the robot's climbing stairs and the engineer is tugging on a rope that's pulling it back down the stairs. you know, 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. So really testing in all conditions, preserving the system in all kinds of ways. And as a result, creating some epic videos, the legendary... The fun part, the hockey stick.

1:15:32And then, yes, talking on spot is just trying to open the door. I mean, it's great testing, but it's also... I don't know, it's just somehow extremely compelling demonstration of robotics in video form. 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, you know, 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.

1:16:21The limits of the system, the challenge isn't involved and failure, if it's showing both failure and success, makes you appreciate the success. Yeah, and then just the way the videos are done in both academics are incredible because they're not there's no flash There's no extra like Production is just raw testing of the robot Well, you know, I was the final edit for most of the videos up until Until about three years ago or four years ago and You know my theory of the video is no 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.

1:17:04Don'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. Yeah, I mean, people always want to add more stuff, but the simplicity of just do something we're showing and show it. That's brilliant. And don't add extra stuff. Now 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's a human, so they were thinking about autonomy, Whereas we were thinking about the mobility.

1:17:57And 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. But also just show cool stuff in this raw form, the limits of the system, the see the system be perturbed and be robust in resilient and all that kind of stuff. And dancing with some music.

1:18:23Intrepidness and fun. So intrepid. I mean, it might be the most important ingredient. And that is, you know, robotics is hard. It's not going to work right, right away. So don't be discouraged. This is all it really means. So usually when I talk about these things, I show videos and I show a long string of outtakes, you know, and you have to have courage to be intrepid when, you know, so hard to build your machine, you know, and then you're trying and it just doesn't do what you thought it would do, what you want it to do. And you know, you have to stick to it and keep trying. How long, I mean, we don't often see that the story behind Spot and Atlas, how long, how many failures was there a long way to get it, you know, a working Atlas, a working spot in the early days, is even working big dog.

1:19:17There's a video of Atlas climbing three big steps, and it's very dynamic, and it's really exciting, real accomplishment. It took 109 tries, and we have video of every one of them. You know, we shoot and everything. Again, we, this is at Boss 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, you know, performance, not everything along the way. But everything along the way is informative and you know, it shows sort of 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.

1:20:13But that's fun. Yeah. So the hardware failures and maybe some software. Lots of control of evolution during that time. I think it took six weeks to get that there's 109 trials. You know, because there was programming going on. It was actually robot learning, but there were human and the loop helping with the learning. So all data driven. But, okay. And so, and you always are learning from that failure. So, right. And how do you protect Atlas from not getting damaged from 109 attempts? 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.

1:21:03And it doesn't break every time. It still breaks and we had you know 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 You know I sometimes criticize the people who have their gold -plated thing and they keep it on the shelf and everybody and they're afraid to Kind of use it. I don't think you can make progress if you're working that way You know you need to be ready to have it break and and go in there and fix it. It's part of the thing You know plan your budget so you have spare parts and a crew and all that stuff. Yeah, if it falls 109 times, it's okay.

1:21:39Wow. So, intrapid, truly, and that applies to spot, that applies to all the other ones. Everything. I think it applies to everything anybody tries to do that's worth doing. Yeah. In a special systems in the real world, right? Yeah. And so fun. Fun. Technical fun, I usually have technical fun. I think that life as an engineer is really satisfying. I think you get to, you know, to some degree, it can be like craft's work where you get to do things with your own hands or your own design or whatever your, you know, your media is. And it's very satisfying to be able to just do the work. Unlike, you know, a lot of people who have to do something that they don't like doing, I think engineers typically get to do something that they like.

1:22:26And there's a lot of satisfaction from that. Then there's, you know, in many cases you can have impact on the world somehow because you've done something that other people admire, which is different from the craft fun of building a thing. So that's the second way that being engineers good. I think the third thing is that if you're lucky to be working in a team where you're getting the benefit of other people's skills that are helping you do your thing. You know, none of us has all the skills needed to do most of these projects. And if you have a team where you're working well with the others, that can be very satisfying.

1:23:08And then if you're an engineer, you also usually get paid. So you get paid four times in my view of the world. So what could be better than that? Get paid to have fun. I mean, what do you love about engineering? When you say engineering. What does that mean to you exactly? What is this kind of big thing that we call engineering? I think it's both being a scientist or getting to use science at the same time as being kind of an artist or creator because you're making some you know scientists only get to describe to study what's out there and engineers get to make stuff that didn't exist before and so it's really I think a higher calling even though I think most you know the public out there think science is top And engineering is somehow secondary, but I think it's the other way around.

1:23:54And at the cutting edge, I think when you talk about robotics, there is a possibility to do art in that you do like the first of its kind thing. So then there's the production at scale, which is it's so beautiful thing, but when you do the first new robot or the first new thing, that's the possibility to create something totally new. that is bringing metal to life or a machine to life is kind of is fun and you know it was fun doing the dancing videos where got a huge you know public response we're going to do more we're going to do some doing some at the institute and we'll we'll do more with that metal to life moment I mean to me that's still magical like when when inanimate objects comes to life that's still like to me It's because this day is still an incredible moment.

1:24:46The human intelligence can create systems that instill life or whatever that is Into an inanimate object. It's really it's truly magical. Especially when it's at the scale of The humans can perceive and appreciate like directly But I think sort of with it going going back to the pieces of that You know you design a linkage that turns out to be half the weight and just as strong, that's very satisfying. And you know, there are people who do that. And it's a creative act. What do you as the most beautiful about robotics? Sorry for the big romantic question. I think having the robots moving away that's evocative of life is pretty exciting.

1:25:36So the elegance of movement? Or if it's a high performance act, where it's doing it faster bigger than other robots. Usually we're not doing it bigger faster than people, but we're getting there in a few narrow dimensions. So faster, bigger, smoother, more elegant, more graceful. I mean, I'd like to do dancing that starts, you know, we're nowhere near the dancing capabilities of a human. We've been having a ballerina in, who's kind of a well -known ballerina, and she's been programming the robot. We've been working on the tools that can make it so that she can use her way of talking, you know, way of doing a choreography or something like that, more accessible to get the robot through things and starting to produce some interesting stuff.

1:26:26Well, we should mention that there is a choreography tool. There is. I mean, I guess I saw versions of it, which is pretty cool. you can kind of at slices of time control different parts at the high level the movement of the robot we hope to take that forward and make it you know more tuned to how the dance world wants to talk wants to communicate and and get better performances I mean that a lot but there's still a lot possible and I'd like to have performances where the robots are dancing with people. So right now almost everything that we've done on dancing is to a fixed time base. So once you press go, the robot does its thing and plays that thing.

1:27:12It's not listening, it's not watching, but I think it should do those things. I think I would love to see a professional ballerina, like a lone and a lone with a robot slowly teaching the robot. Just actually the process of a clueless robot trying to figure out a small little piece of a dance. So it's not like, because right now Atlas and spot have done like perfect dancing to a beat and so on. So you know, to degree. But like the learning process of interacting with the human would be like incredible to watch. One of the cool things going on, you know that there's a class at Brown University called career robotics.

1:27:53Sydney Skybetter is a dancer, a choreographer, and he teamed up with Stephanie Telax, who's a computer science professor, and they taught this class, and I think they have some graduate students help and teach it, where they have two spots, and people come in. I think it's 50 -50 of computer science people and dance people, and they do program performances that are very I show some of them sometimes when I give a talk and making that process of a human teaching the robot more efficient more intuitive Maybe you parse language part movement That'd be fascinating. That'd be really fascinating because I mean one of the things I've kind of realized is Humans communicate with movement a Lot it's not just language.

1:28:41There's a lot of this body language. There's so many intricate little things and totally And like that, you know, to watch a human and spot, communicate back and forth with movement is, I mean, there's so many wonderful possibilities there. But it's also a challenge, you know, we get asked to have our robots perform with famous dancers. And they can, you know, they have 200 degrees of freedom or something, right? every little ripple thing and they have all this head neck and shoulders and stuff. And the robots mostly don't have all that stuff and it's a daunting challenge to not look stupid, you know, physically stupid next to them.

1:29:26So we've pretty much avoided that kind of performance. But we'll get to it. I think even with the limited degrees of freedom, we could still have some and some sass and flavor and so on, you can figure out your own thing, even if you can't. And we can reverse things. Like, if you watch a human do robot animation, which is a dance style, where you jerk around, sort of, you pop and pop and lock and all that stuff, I think the robots could show up the humans by doing unstable oscillations and things that are faster than a person could do. So that's sort of on my plan, but we haven't got quite gotten there yet.

1:30:07You mentioned about building teams and robotics teams and so on. How do you find great engineers? How do you hire great engineers? I think you even need to have an environment where interesting engineer, well, you know, it's a chicken neck. If you have an environment where interesting engineering is going on, then the engineers wanna work there. And, you know, I think it took a long time to develop that at Boston, I know. 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 of an engineering than compared to what boss dynamics is now.

1:30:46But it was our ambition to do that. And Sarko was another robot company. So I always thought of us as being on the computing side and this much on the hardware side. And they were like this. And then over the years, we, you know, I think we achieved the same or better levels of engineering. Meanwhile, you know, Sarcus got acquired and then they went through all kinds of changes. And I don't know exactly what their current status is, but... So it took many years as part of the answer. I think you got to find people who love it. In the early days, we paid a little less, so we only got people who were doing it because they really loved it.

1:31:31We also hired people who might not have professional degrees, you know, people who were building bicycles and building kayaks. We have some people who come from that kind of the maker world. And that's really important for the kind of work we do to have that be part of the mix. whatever that is, whatever the magic agree and that makes a great builder maker. Yeah, that's the big part of it. People who repair the cars or motorcycles or whatever in their garages when they were kids. There's a kind of like the robotics students, grad students, and just robotics that I know and hang out with. There's a kind of endless energy.

1:32:13Like, they're just happy. Like say, I compare it to another group of people that are like that are people that skydive professionally. There's just like an excitement and general energy that I think probably has to do with the fact that they're just constantly. First of all, fail a lot. And then the joy of building a thing that eventually works. I'm talking about being happy. There used to be a time when I was doing the machine shop work myself back in those JPL and Caltech days. when if I came home smelling like the machine shop, you know, because it's an oily place. My wife would say, oh, you had a good day to have a cutie good tell.

1:32:51That's where I've been. You've done, you've, yeah, you've actually built something. You've done something in the physical world. Yeah, and probably the videos help, right? The videos help show off what robotics is. Oh, you know, at Boston Dynamics, it put us on the map. We, I remember interviewing some sales guy. And he was from a company and he said, well, no one's ever heard of my company, but we have products. You know, really good products. You guys, everybody knows who you are, but you don't have any products at all, which was true. So it was, and you know, we thank YouTube for that. YouTube came.

1:33:30We caught the YouTube wave and it had a huge impact on our company. I mean, it's a big impact on not just the new company, but on robotics and general. and helping people understand and inspire what is possible with robots. The inspire imagination, fear and everything. The full spectrum of human emotion was a rose, which is great for the entirety of humanity. And also, it's probably inspiring for young people that want to get into AI robotics. Let me ask you about some competitors. Sure. You've been a complimentary of Elon and Tesla's work on Optimus Robot. What do you think of their efforts there with the humanoid robot?

1:34:15I really admire Elon as a technologist. I think that what he did with Tesla is just totally mind -boggling. 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 if you could. 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.

1:35:10You know, I've visited a figure. I think they're doing well and they have a good team.

1:35:17I've visited an electronic and I think they're, they have a good team and they're doing well. But Elon has a lot of resources. He has a lot of ambition. I'd 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. Do you think Atlas and Optimus will hang out at some point? I would love to host that. Now that I'm not at Boston Dynamics, I'm not officially connected. I am on the board, but I'm not officially connected. I would love to host a robot meetups. I wrote that made up, yeah.

1:35:59Does the AI Institute work with spots and Atlas is a focus on spots mostly right now as a platform? We have a bunch of different robots. We bought everything we could buy. So we have spots. I think we have a good size fleet in them. I don't know how many it is, but a good size fleet. We have a couple of animal robots. You know, animals a company founded by Marco Harder, even though he's not that involved anymore, but we have a couple of those. We have a bunch of arms like, you know, Frank is in the US robotics Because you know even though we have ambitions to build stuff and we are built starting to build stuff You know they won getting off the ground.

1:36:39We just you know just bought stuff I love this like robot playground. You've built You come over and take a look at you. That's great. So it's like all these kinds of robots, legged arms It doesn't feel that much like well, there's some areas that feel like a playground, but it's not like they're all frolic to get there Hey again, maybe you'll arrange it a robot meetup But in general, what's your view on competition in the space for especially like humanoid and like a robots? Are you are you excited by the competition or the friendly competition? I? think that But it doesn't, I don't think about competition that much.

1:37:23I'm not a commercial guy. I think for many years, the many years I've been said, Boston Dynamics, we didn't think about competition. We were just doing our thing. There wasn't like there were products out there that we were competing. Maybe there was some competition for DARPA funding, which we got a lot of, got very good at getting. But even there, in a couple of cases where we might have competed, we ended up just being the robot provider. That is for the little dog program. We just made the robots. We didn't participate as developers, except for developing the robot. And in the DARPA Robotics Challenge, we did compete.

1:38:05We provided the robots. So, you know, in the AI world now, now that we're working on cognitive stuff, it feels much more like a competition. You know, the entry requirements in terms of computing hardware and the skills of the team are, and hiring talent, it's a much tougher place. So I think much more about competition. Now on the cognitive side, on the physical side, it doesn't feel like it's that much about competition yet. Obviously, with 10 humanoid companies out there, 10 or 12, I mean, there's probably others that I don't know about. They're definitely in competition. We'll be in competition.

1:38:50How much room is there for quadruped and especially a humanoid robot to become cheaper? So like cutting costs and like how low can you go? And how much of it is just mass production? So questions of, you know, Hyundai, like how to produce versus like engineering innovation, how to simplify it? I think there's a huge way to go. I don't think we've seen the bottom up at the bottom in terms of lower prices. I think you should be totally optimistic that at asymptote things don't have to be any like as expensive as they are now. Back to competition, I wanted to say one thing. I think in the Quadruped Space, having other people selling Quadrupeds is a great thing for Boston Dynamics.

1:39:40Because the question, I believe the question in the user's minds is, which Quadruped do I want? It's not, oh, do I want a Quadruped, can a Quadruped do my job? It's much more like that, which is a great place for it to be. Then you're just doing the things you normally do to make your product better and compete selling and all that stuff. And that'll be the way it is with humanoids at some point. Well, there's a lot of humanoids and you're just not even... It's like a... It's... ...phoen versus android and people just buying both and it's kind of just... Yeah. You're not really... You're creating the category.

1:40:18Yeah. Or the category is happening. I mean, right now, the use cases, you know, that's the key thing. having realistic use cases that are money making in robotics is a big challenge. You know, this is the warehouse use case. That's probably the only thing that makes anybody any money in robotics at this point. There's got to be a moment. There's old -fashioned everybody. I mean, there's fixed arms doing manufacturing. I don't want to say that they're not making money. It's industrial robotics, yes. But there's got to be a moment when social robotics starts making real money, meaning like a spot type robot in the home.

1:40:54And there's tens of millions of them in the home and they're like, no, I don't know how many dogs are in the United States as pets It feels many it feels like there's something we love about having a Intelligent companion with us that remembers us that's excited to see us all that kind of stuff But it's also true that the company's making those things. There've been a lot of failures in recent times, right? There's that one year when I think three of them went under So it's it's not that easy to do that right Getting, you know, getting performance, safety, and cost, all to be where they need to be at the same time, is that's hard.

1:41:35But also some of it is like you said, you can have a product, but people might not be aware of it. So like also part of it is the videos are however you connect with the public, the culture and create the category. Maybe people realize this is the thing you want. Because from a you know, there's a lot of negative perceptions you can have do you really want a System with the camera in your home walking around right If it's presented correctly and if there's like the right kind of boundaries around it They understand how it works and so on that a lot of people would want to and if they don't that might be suspicious of it So that that's important like we all use smartphones and that as a camera that's looking at us No, yeah It has two or three or four.

1:42:19And it's listening. Isn't it a very few people are suspicious about it. They kind of take it for granted and so on. I think robots would be the same kind of way. I agree. 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 and 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 need a menu of detailed categories to come up with that.

1:43:09But I also think that the conversation that seems to be happening about AGI is puzzles me. It's sort of, so I ask you a question. Do you think there's anybody smarter than you in the world? Absolutely, yes. Does it do you find that threatening? No. So I don't understand even if computers were smarter than people, why we should assume that that's a threat. Especially since they could easily be smarter but still available to us or under our control, which is basically how computers generally are. I think the fears that there would be 10X, 100X smarter and operating under different morals and ethical codes that humans naturally do.

1:43:59And so almost become misaligned in unintended ways and therefore harm humans in ways which can't predict and even if we program them to do a thing as on the way of doing that thing, they would cause a lot of harm and when there are a hundred times, a thousand times, 10 ,000 times smarter than us, we won't be able to stop it or we won't be able to even see the harm as it's happening until it's too late. That kind of stuff. So you can construct all kinds of like possible trajectories of how the world ends because of super -entire systems. It's a little bit like that line in the Oppenheimer movie where they contemplate whether the first time they set off a reaction all matter on Earth is gonna go up.

1:44:47I don't remember what the verb they used was for the chain reaction, right? Yeah, I guess it's possible, but I don't think I I personally don't think it's worth worrying about that. I think that the, you know, it's an opportunity, balancing opportunities in risk. I think if you take any technology, there's opportunity in risk. And you know, it's easy to, I'll point at the car. They pollute and they, about what, 1 .25 million people get killed every year around the world because of them. Despite that, I think they're a boon to humankind, very useful. Many of us love them. Those technical problems can be solved.

1:45:36I think they are becoming safer. I think they're becoming less polluting, at least some of them are. Every technology you can name has a story like that in my opinion. What's the story behind the Hawaiian shirt? Is it a fashion statement, philosophical statement, is it just a statement of rebellion? Engineering statement. It was born of me being a contrarian. Yes. Someone. This is a symbol. Someone told me once that I was wearing one when I only had one or two, and they said, oh, those things are so old fashioned, you can't wear that mark. And I stopped wearing them for about a week. And then I said, I'm not going to let them tell me What to do and so every day since pretty much so it's like a year ago that was 20 years ago 15 years ago probably Oh, that's something why your personality is great as you're not Took me a while to realize I was a contrarian, but you know it can be a useful tool Have you had people tell you about on the robotic side that like I don't think you could do this The kind of negative motivation

1:46:49I'd rather talk about, there's a guy, when we were doing a lot of DARPA work, there was a Marine Ed Tovar who's still around, who, what he would always say is when someone would say, oh, you can't do that, he'd say, why not? And it's a great question. I ask all the time when I'm thinking, oh, we're not going to do that. And I say, why not? And I give him credit for opening my eyes to resisting that. So yeah, the Hawaiian shirt is almost like 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 that can be proud of, how they can have a career that can be proud of?

1:47:34When 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 would you imagine doing? And I said, well, start there and see how close you can get. 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. Because I don't think a lot of people think that they're in a channel, right?

1:48:19And there's only limited opportunities. But it's usually wider than they think. Yeah, the opportunities really are limitless. But at the same time, you want to pick a thing, right? And it's the diligence and really, really pursue it, right? Really pursue it. Because sometimes the really special stuff happens after years of pursuit. Yeah. Oh, absolutely. It can take a while. I mean, you've been doing this for 40 plus years. Some people think I'm gonna write, right? Why don't I do it? And in fact, some of the inspiration for the AI Institute is to say, okay, I've been working at a local motion for however many years it was.

1:49:06Let's do something else. And it's a really fascinating and interesting challenge. And you're hoping to show it off also in the same way as just about to start showing some stuff off, yeah. I hope we have YouTube channel. I mean one of the challenges is it's one thing to show athletic skills on YouTube. showing cognitive function is a lot harder and I haven't quite figured out yet how that's going to work. There might be a way. There's a way. There's a way. Why not? I also do think sucking at a task is also compelling. Like the incremental improvement, a robot being like really terrible at a task and then slowly becoming better, even in a fledic intelligence honestly, like learning to walk and falling and slowly figuring that out.

1:49:57I think there's something extremely compelling about that. We like flaws, especially with the cognitive task. It's okay to be clumsy. It's okay to be confused and a little silly and all that kind of stuff. It feels like in that space is where we can... There's charm. There's charm. There's charm and there's something inspiring about a robot sucking and then becoming less terrible slowly. I think you're right. That kind of reveals something about ourselves. And ultimately that's what's one of the coolest things about robots is it's kind of a mirror about what makes humans special. Just by watching a heart is just to make a robot do the things that humans do.

1:50:42You realize how special we are. What do you think is the meaning of this whole thing? Why are we here? Mark, you have asked about the big questions as you try to create these humanoid human -like intelligence systems. I don't know. I think you have to have fun while you're here. That's about all I know. It would be a waste not to, right? The ride is pretty short. Somebody as well have fun. Mark, I'm a huge fan of yours. It's a huge honor that you would talk with me. This is really amazing and your work for many decades has been amazing. I can't wait to see what you do at the AI Institute. I'm going to be waiting impatiently for the videos and the demos and the next robot meetup for maybe Atlas and Optimus to hang out.

1:51:35I would love to do that. That would be fun. Thank you so much for talking to it. Thank you, it was fun talking to you.