Marc Raibert: Boston Dynamics | MIT Artificial Intelligence (AI)

welcome back to six at $0.99 artificial general intelligence today we have mark raybert he is the he really doesn't need an introduction but we'll give him one anyway he's the founder and CEO CEO of Boston Dynamics he founded the CMU like lab in 1980 the MIT leg lab in 1986 Boston Dynamics in 1992 he and his team have developed some of the most amazing robots ever built including Big Dawg Atlas handle spot spot mini these robots move with the agility dexterity and even grace that rivals and often supersedes that of human movement he continues to inspire us with what robots are capable of achieving in the real world and what physical form future intelligence systems may take as they become integrated in our daily lives so please give mark a warm welcome [Applause] this is our grand mission our aspiration which is to make robots that are equal to or greater than people and animals and it's you know it's a daunting mission because we're so good at things it seems effortless you know I'm standing here knowing questions that I could stand here like this but a lots going on I can manipulate things I can pick up this water or I could reach in my pocket and use my hands with all the sensors in my hands and coordinate that and maybe most of all our perception systems you know this audience has what is it 250 people in it or something and I can look out there and see every one of you stabilized in space even while I'm moving it's it's just astounding and you know robots aren't there yet but I think they can be and our goal is to keep chipping away to try and get there before I get started I wanted to say that I got my start in robotics here at MIT I was a graduate student I was in the what was then called the psychology department the brain and cognitive sciences department but I was taking an AI AP course just like you are and it might have been you know exactly this time of year when I followed one that my professor Burt old horn back I had so I was jabbering away out I'm asking him some question about this or that and we walked back to tech square which is where the AI lab was in those days and we went up to the ninth floor and Russell nafse Kerr who was a guy working in the lab had an arm all taken apart on the table it was like a thousand pieces and I was a roboticist from that day on I swear I didn't switch my major but I you know got Burt old to be an advisor I found a topic that had to do with robotics in that time it was a manipulation thing but eventually became legged thing and it was amazing you know and I've never looked back so here are some animals doing things that are very exciting climbing around on very rough terrain very sure-footed using a mixture of their proprioception and their vision and look there's even a baby that probably is only a couple of months old has no trouble at all doing these things and look at the Grace and suppleness and the fearlessness of these animals it's amazing here are animals running for their lives the Gazelle is trying to stay alive for the next ten minutes and the cheetah is trying to get a meal so that it can stay alive in general sorry and you know even people can do things that a breath take I assume all of you were out this morning getting a little exercise climbing up the green building that we're in now and and maybe the other places around here it's funny I bumped into some people when I came into the room who were climbing the stairways I think they were going on a trek up and down them but I'd like to see the going outside so probably most of you have seen this video this is uh this is sort of where we were after about ten years of work attempting to make machines that could work out in the real world that were dynamically stabilized dynamics is a big deal for our company and for what we do so some active sensing and control and understanding of the physics here this robot has all its control onboard and it has reflexes and sensors and this is an extension to a thousand-pound robot that could carry about 400 pounds of payload and we took it all around the United States testing it in various situations here we have it in Virginia doing some bushwhacking it's actually following a person but the person is only in that of you intermittently so it has to be able to keep track of where the person is and deal with that and then back in good old Boston ten inches of snow just marches right up the hill here's the cheetah now you know MIT has its own cheetah this is our cheetah the people know song Bay who was doing the MIT cheetah a very dynamic machine and basically an experiment in seeing how fast we could make something like this run although you notice it's on a parking lot so it wasn't doing this on rough terrain and getting both the efficiency and the speed in in the context of a machine they'd also can do rough terrain is a really big challenge that remains with us so this is just a snapshot of most of the robots that we've built at Boston Dynamics over the years and I'm not going to talk about most of them I'm just going to talk about the last four these are all robots that we developed since we've been part of Google which has been the last four years spot mini there's a spot mini on the floor here which will demo a little later spot Atlas the humanoid some of you may remember the humanoid that we used in the DARPA Robotics Challenge you have one here and and then handle which is our latest version so I'll say have a few words to say about each of them so we had been developing a big dog and those other quadrupeds that I showed you for quite some number of years and it was amazing for us to find out when we did this project on on spot this is the predecessor to that that there was still a lot to learn and we kind of revolutionized the hardware design and how the control worked and got a much higher level of rough terrain performance and part of the solution to that was to be able to decompose the control problem into many separate controllers that operated in different regions of state space and that allowed us both to have programmers work on multiple solutions to the problem and also have the complexity of each controller simplified by only having to operate in a small part of the dynamic space here we've added a robot arm to the to the previous version of spot and you know we believe that mobile manipulation that is manipulation when you can move the base is really a powerful way of doing things now this is probably the most important thing I want to show tonight and I'll show it three different times the idea that we don't build controllers that just do one particular thing but that they can determine where they are in the execution here's another version of it and then adjust what they're doing in order to compensate for disturbances in the real world I know this class is about AI and probably autonomy I think that the one of the most important ways of getting to autonomy is to have the low level implementations very robust to disturbances so that the planning steps don't have to take care of all the minutiae of the details of the real world and that's what we've been trying to do there we've been experimenting with doing delivery of packages to people's houses these are all employees of Boston Dynamics so we didn't go crashing ordinary people's houses and it turns out that there's just lots of different kinds of stairways and entranceways and the robots doing very well we're up to something between seventy and eighty percent of of the kinds of stairs and access places we encounter after collecting data and making improvements and adjustments so I'm going to say if you philosophical things or approach things a lot of people think that this is the model of how a computer and a robot interact that is there's the robot which is hardware and electronics and sensors and and then there's a computer and that the computer listens to the sensors on the robot and then gives it instructions and tells it what to do and well I think that's actually going on there's another part to the story which is that the physical world is also giving instructions to the robot and that means that the energy is stored in the robot either in its Springs or in its it's motion those are all important determinants of how the robots going to behave in the time coming forward and so we like to think in terms of designing the hardware of the robot the physical world and the computer all as one holistic thing where we take into account those interactions sometimes we call this a harmony you know a harmonic system is one usually where you have energy oscillating back and forth almost all legged locomotion has some amount of harmony going on between potential energy of elevation potential energy of elastic deformation kinetic energy of motion and you know inverted pendulum things and the like another part of our approach we call build it break it fix it now I have friends who build their robots and are so into the the beauty of what they've created that they kind of put it on an altar and afraid of actually hurting it so in fact I even have friends here at MIT that have done that where they have a gold-plated robot and they're afraid of taking it out into the world I mean we're just the opposite every one of our robots is designed to get bashed to bits we have staff who are there to fix the robot on a daily basis as we break it and I think doing that build it break it fix it means that we're able to learn a lot from the actual physical robot working in the world and we can use that knowledge in order to improve the robot improve its behavior and we really like to go around that loop as quickly and as we can early in the in the process and do it as many times as we can so here's what build it break it fix it looks like this is in Somerville our engineers this is um a Boston driver now this robots supposed to be using its visual system to avoid the trees I think it might have fallen in love with this tree we don't purposely give them any emotion but boy it's hard not to see that and here's the first time we tested the the push response to this robot hey did you hear that that's the new guy's car so some guy we just started that week Trent had $5,000 which we paid for in in repairs to his a vintage BMW so the last thing sort of about philosophy is long-term versus short-term you know our company is 25 years old and we've mostly been a long-term robotics company that is we're interested in moving the boundary forward in what what robots can do and we're interested in you know making it so robots meet the dream of being the equal or better than people and animals but now we've started function [Music] okay we still on can you hear me but lately we've started to realize that some of our robots have enough capability that maybe it's time to try and productize them and we will learn a lot by doing that too one of the things for instance that I've always claimed is that we always spent a lot of money on building our robots in them and use that as a competitive advantage that is DARPA was a frequent funder of us DARPA always said let's take money out of the equation and just figure out you know how to get the solution and then worry about getting the cost down later so I always assumed and argued that once we get a robot doing things that are interesting then you can go and redesign it to make it lower cost well we're going we're going to test that because it might not be true it might be that we've designed ourselves into an expensive corner and that it might be too late but the robot that was showing a little bit is much significantly cost reduced from the prototype of it and it'll be interesting to see whether we could get it down to the kind of prices that are useful so this is just a picture again of the idea of aiming long but also aiming short and I think it's going to be a challenge to see whether we can keep the culture of the company to support both of these directions because people manufacturing stuff have a different mindset than people trying to get out to the future horizons and it's going to be a challenge to keep both those kinds of people happy here's some of the things that some of the kinds of applications you can look at based on modest technical capabilities I've shown mobility and manipulation here but you could put cost reliability there's many things that could be on these axes you know entertainment like robots and theme parks is something that I think we should be able to do I already talked about home delivery I think home delivery is waiting for self-driving cars to get all the way there self driving trucks and once they do then we will be working on getting it from the truck to the to the home logistics there's about a trillion boxes moved every year around the world and most of it's done by hand and so there's really a big opportunity to having robots help with moving those trillion boxes security which could mean either commercial security like patrolling your shopping center or the military type security construction a lot of people have been coming to us with their construction applications asking if we can help and you know I'm not going to talk about it now but if afterwards you want to ask about that I can fill you in a little more and I think this is really the ultimate home run application care for the elderly and the disabled I used to say that I wanted to have robots that would help me take care of my my parents and older people but I realize now that it's probably going to be my children using them to help take care of me but you guys all you're all a little bit younger and I think there'll be a time when you could use robots to help make your parents lives better now some of you may think that your parents don't want that but I think it's a complex question we've seen some surveys that say that you know people aren't totally happy with the idea of their kids taking care of them on a moment-by-moment basis and I think there's going to be an opportunity for doing something but technically this is still a ways off it's it's a tough thing okay let's get back to the robots spot Mini is a robot that weighs about 60 pounds that previous spot weighed about 180 pounds this one weighs about 60 pounds and here's some Anatomy it's got an arm with five degrees of freedom each leg has three degrees of freedom it's got about a 500 watt our battery batteries for these things are a challenge because you know can have consumer products like electric drills that have relatively small batteries and then there's electric cars that have big batteries and there's not really much available in between so we've done a lot of work on the battery technology for these things to make them safe and reliable and hot swappable and things like that then there's radios and computers the previous version had three quad core i7s this one has two we're trying to cut back on the cost and then there can be some sensors lidar s stereo and the like so you can see spot minis a little bit smaller than spot this isn't a real house and those aren't real people those are engineers this is inside of a warehouse we have out on 128 where we've built the house you can see that they don't we don't mind scuffing up the walls here and there is a lot of scuffing that happens some of you may recognize ACTU Kowski who's a an MIT alum and he's again disturbing the robot here the robots using its vision to do some stepping stone type operations and I think gene is going to talk a little bit more about this in a couple of minutes and here's a case where it's doing stepping stones on real stones and it's keeping its balance figuring out where to put the feet and again this robot only has stereo looking out the front whereas this one has stereo on all four sides now one of the cool things about animals is that they have these stabilization mechanisms for their sensors that was a real chicken no robotics involved and here's our attempt to show that these this robot can do the same sort of thing and if you think about it when you're manipulating you really want the hand to be stabilized in space and so you'd like the body to be able to kind of coordinate with the hands so that you can concentrate on what the world real-world task is man you guys didn't pick up the banana peel huh so our concept for the spot mini product is to make a platform it's sort of the we're thinking of it like the Android of robots so with Android there's a hardware platform and then there's a software platform and then developers third-party developers create their own apps that use the platform so we've made this spot so that there's a place to mount hardware on the robot but there's also an API to program it through and then there's a facility to have additional computing external to the robot and we're working with third parties to develop their own applications that run on the platform this is a video that we haven't been able to release publicly please don't tape it and show it because I can't I'll explain later if you want to know why not but this is just a revealing that we do have an arm on the new version of spot it's using a camera in the hand to find the the door handle this robot doesn't weigh a lot so it has to use tricks to keep the door open so that's why puts his foot in the door and here again we want to show that the we've made the solution robust to certain kinds of disturbances so Andy there Andy sitting over here is pushing on the door pushing on the hand the robot keeps track of how far how much progress that's made in doing its task it's so it's so smart it even kicks that that shell out of the way now that was a total accident and now it's just going back to try again okay and then this is a demo of autonomy here the robot has in a previous session we've taken it around the lab this is Boston Dynamics taking them around the lab and recorded visual data that could be used for navigation and it's using its stereo to match up features in the environment so that it can navigate and go where it had gone in the previous on the previous path so there's no one driving it for this it's all autonomous that was outside my office every day around noon the robot seems to show up and I hear it pausing out there I don't know why it turned there sometimes it comes up with a solution that isn't in here you'll see another one it comes up with a solution that isn't quite what you call is an optimization but it does it does get a solution so we're pretty excited by this we call this patroller out and we're working on developing a lot of software to support it to make it so that other people can capture a patrol route and then execute them on a on a routine basis and then do two other tasks while they're on the on the patrol route Seth you're on so we're at will do a demo of spot mini so for these for this demo Seth's got a joystick and he's telling it the speed to go in the forward direction and turning but the robots doing all its own gate selection coordination of legs balance obviously so the robot has a bunch of different gates it can walk here it's doing one leg at a time it can trot I know you do whatever gates you want except he's got to use a selective so here's trotting which is diagonal pairs of legs it can do pacing which is lateral pairs of legs to get working together I have to tell you in the earliest days of me being involved in legged locomotion I thought gait was a big deal but it's really kind of a small thing and I don't think it's central to what matters which is support stability propulsion and things like that I'm gonna wrap up shortly I just thought I'd say a couple of words about the mechanical side you know the Atlas is a new version of a humanoid I know some of you worked with the DARPA Robotics Challenge humanoid which was a big hulking thing that we made and this is a much more svelte one and the way we got there was to work on the elements of the mechanical design to take advantage of 3d printing and some optimization and we did we focused on two or three different things one is making some of the leg parts where we embed hydraulic pathways hydraulic actuators places for valve mounts and filters and things like that into the leg and this is what that looks like there's a single upper leg part that incorporated about 15 or 20 different separate components in the previous design which made it lighter more compact and higher strength to weight ratio we also developed a hydraulic power unit which takes many components the thing on the left are the components as separate ones and we were able to print up parts that integrated them so that there was a motor a pump inside of a motor an accumulator reservoir valves filters and those things and we shrunk it down so that the robot could be smaller and lighter and using that approach we went from about a 375 pound DRC robot to a 190 pound robot and then the current one is about 165 pounds now this picture might lead you to believe that I'm advertising myself is only weighing 165 pounds and I'm fortunately that's not true but I'm working on it but it is close to my size and weight and I don't know I don't think we have this out as a video here's some robot behavior that uses whole body motion meaning the mobility base plus the arms plus the torso are all combining in order to handle these these boxes it's using vision with the QR codes to simplify the task here we're trying to go at human speeds of operation and so the robot searches for a box using its vision I think that I think that was the only take we ever got with both robots working together and you know one of the problems with YouTube is everybody's already seen what you've been up to by the time you get it go around to give a talk so I imagine most of you have seen this but here's a parkour robot we're working on where we've actually strengthened the hips so that it can do a little bit more jumping and and it's a kind of interesting that we've been interested in making a robot a little bit like the humanoid that has less degrees of freedom fewer degrees of freedom and the simpler and we designed this robot and the ultimate version of this we'll have about 10 joints whereas the humanoid had 28 and have many many of the same capabilities we have some use cases for this that I'm not going to talk about today but this robot can lift heavy loads it has a relatively small footprint given what its strength is so the way things are done in logistics now is to use big robot arms that take up a lot of floor area or heavy and we're looking at ways of using a robot like this one not exactly this we it's sort of any evolution of this design in order to do logistics operations so I want to make a pitch to you Boston Dynamics is hiring and I hope some of you will apply for a job there these are how many is it 6 x 3 these are 18 MIT alum that currently work at the company many of them for many years so I'm sort of making the point that these people are happy they're just like just like you could be and I hope you'll look at our website and see what we're what we're looking for and considerate so I'm just gonna wrap up by talking about you know I used to be a professor here and at Carnegie Mellon and when I was the professor we used to mostly wrote papers and we were excited by you know how many papers we could write and how many people cited them in their papers but as a company guy instead of papers I think we count YouTube hits and instead of citations here I want to tell you what this is but most of you probably know so now we count now we count spoofs instead of citations and I'm happy to say that we're doing great we have about about two dozen BigDog spoofs here's four of them and the upper left is in Akihabara Japan the upper right is a Los Angeles online television show it's the Netherlands on the lower left and I guess that's Appalachia on the right the poor kid doesn't even have a friend to to be in his movie well what about what about Atlas can you hear that [Music] here's it here's another one [Applause] so we have we have a big crew working on all these projects you've you've gotten to meet a couple of them here but it's really quite a team in a an absolute pleasure to work with so anyway thank you [Applause] [Music] thanks for the presentation it was amazing what sort of physics simulation like if any do you have in your robots and do you really think that like with the current trend of neural networks we can just like do end-to-end modeling of these robots with like without any sort of notion of physics but just like neural networks so we have simulators that we've worked on for a long time very detailed in some cases validated validated me and compare the behavior of the simulator to the physics of ground truth and you know I think they're important for our work and we use them frequently but the end to end doesn't ring quite true usually the when we use simulation the user is knowledgeable about the trade-offs between doing a physical experiment and doing a simulated experiment and they're usually getting at some specific where specific setup question rather than the idea that you start at one end you know - at least in our experience trying to simulate all the subtleties of the hydraulic actuator back lashing gears flexibility you know the non rigidity in the components that's a big undertaking and usually so so distracting that you can't really get on with with what you're doing so I think we use experiment for those subtleties and we use simulation for bigger level dynamics questions hey would you say mechanical concerns or computational capability is more of a difficulty in terms of determining how quickly you can perform tasks with the robots you know we like to say that they're equally important we we now although we didn't start out this way we now have equal strength in our groups in the mechanical design and implementation and in the software and controls and sensing and I think you know they all matter I think if you try and get by with just marginally designed hardware you don't get my experimental time in because the things broken all the time so even though we are rough on our machines they mostly keep working because because we've put a lot of you know attention to detail and how they're designed but you know there's still that I think perception is still a tall pole in the tent certainly if you want a rival human perception I don't think we're you know were anywhere near there I think the self-driving car stuff is helping there's a lot of interesting things happen there I think specialized Hardware skating you know Asics and and things that could help but you know it's it's all still needed so you guys have developed like various components that all kind of they'll come together to build one robot have you seen applications for any of these separate components elsewhere so organic design for example for the Atlas maybe prosthetics or hip replacements or something like that because there seems to be a lot of development going on and then individually as well as the big picture I mean you're asking a very good question there's a question in case people couldn't hear is aside from value to the whole robot of the components we're making are the components useful some other way and you know the place where we think it's probably most true is the specialized hydraulic components we've made servo valves and the HPU I'm sure we could sell them into other industry I as a company focus question though that's really what it comes to do we really want to be doing that will that absorb too much time and attention and personnel or do we want to you know our heart is really in building you know future generations of robots so I think we're going to probably stay there okay thanks I was wondering have you done any research in regards to getting the robots to perform tasks involving direct physical contact with humans I can only the only thing we've done is we've done teleoperation which is not what you mean where we have a human moving in the robot you know copying which is very interesting because you can see that that's a way of showing how fast the robot can be and how coordinated it can be using a human and for part of the computing but we have we don't have them interacting with people I guess the closest is we once did a thing where a person and a robot picked up a stretcher and work together to pick up the stretcher but they weren't touching each other they were going through the stretcher material do we have plans ah you know we're really to be honest we're really struggling with coming up with some strong concepts for safety even without doing that you know robots it's you know your first reactor stree action and how you make a robot safe if there's a problem don't really work very well you can't freeze the robot you have to find some you have to keep them going find a way to get into a safer state so I think having them in contact with people is just going to be harder so eventually we want to to help you know to carry lift the elderly and things like that but we're not there yet my questions about the relative rates of progress in robotics and machine intelligence so an economist might maybe measure it by seeing how much money is going into computing hardware versus arms and leg sensors and actuators that kind of thing so on one impossible scenario the the machine intelligence rushes ahead and the robots progressing more slowly because of kind of slow build test cycle basically it's their real-world things it's not so easy to get a rapid build test cycle with a robot and in and in the other scenario the robots more advanced than the machine intelligence because machine intelligence is just such a conceptually difficult problem so in one scenario the machines are telling the humans what to do in the other scenario that he telling the machines watch do if you like so do you have any kind of perspective on that whole issue of them is that the machine intelligence folk going to rush ahead being what's the guys struggling behind or the robots going to get there before the massive problem and machine intelligence gets solved or maybe somewhere in the middle I think let's see I don't know exactly what you mean by machine intelligence are you talking about you know having Google do better search computation in general so I start I talked about economists measuring sensors actuators and compute Hardware so that's the kind of thinking about yeah I think that it's always been a misconception that the hardware components by themselves constitute progress in intelligence or in robot behavior they're I think they're important ingredients but by themselves you know when I was a graduate student here I can remember reading an ad for an optical character recognition system and what the ad said was you know we have camera we have a thing for holding the paper you're looking at all you have to do is write the software so it was all done except for you got to write the software and you know it's the the whole problem was there so I don't know if I'm answering your question you know robotics is hard I think it feels like we're making progress if you keep pushing we keep making progress it's not like there's an e and the curve that we've hit but I also think that the rest of the AI world is making a good progress too and it's fun being a part of it hi I my question is mostly related to security so since you are productizing your robots now there has been research on Leiter's mainly where you could spoof a lidar and and the sensor basically cannot see anything so are you looking into that as well taking into consideration these awesome robots that you're building could be in let's say you know defense you know working for the defense as well so those are like really harsh environments yeah I mean these are very hard problems you know if someone if if an intelligent adversary wants to trick the robot it's not all that hard these days you know where we're working probably the other end of the problem you know trying to do the basics right now I don't think you know I don't I don't think robots are going to be as autonomous in a hostile environment as as people either think or fear because of how frail they'll still be until we get further along hi there Hey I want to ask about two things that are going to probably play a big role in adoption the first is price so if you could speak to the current unit price of a spot many and how that you think is going to evolve over time and the second is sort of consumer psychology I felt like when I saw the the test at the end of the robots wearing my level of comfort with it being in my house suddenly shot up it seemed way more human so I was thinking about what kinds of experiment you guys were on where you what you've thought about with respect to making people more comfortable with robots working around them yeah in terms of cost all I you know we're not saying what this thing costs yet but we will later in the year we have reduced the cost of this by about a factor of 10 from what the first prototypes cost so we're making progress in terms of the psychology of robots it's been very interesting to watch you know we we got branded sort of as robot abusers because we kick with our robot really what we were doing was trying to show how good they were at balancing and we weren't we didn't think we were abusing them I have video of me pushing on my daughter when she's one years old and actually knocking her over but that wasn't my goal I wanted to kind of test out her her balance and I bet you you know if you guys have kids or you're at all that you've you've done stuff like that so but we've adjusted a little bit and so we don't usually push on the robots in our videos despite the one we showed with the hockey and the hockey sticking hand on this thing that's why we had the banana peels as a way to have the robot crash without us being having our finger prints on it you know I I guess the other data point I have is that if you look at the likes and dislikes on our YouTube videos we found a way to get the likes to dislikes ratio much higher by partly probably by not looking like we're abusing the the robots there's probably a long way to go to make these things really friendly and I have to admit there's a little spirited of our cut at our company of being kind of you know it's fun being bad boys in terms of you know just make the robot do cool stuff and leave the the emotions to others and certainly the social robots that have so much going into making them cute I don't know I'm sure we'll have marketing people working on that I don't know what else to say hi general questions so in terms of research purpose or like practical purpose so what are the reasons that we choose to investigate on these humanoid robots so it seems like it cannot run as fast as the cheetah and it also cannot carry as many stuff as the big dog yeah you're you're basically saying that the humanoids don't seem to be as practical in terms of functional right so is it more efficient like like a humanoid robots more efficient than they start cheetahs and the big dogs well you know the motivate so I don't have a good answer the motivation for the DRC the DARPA Robotics Challenge which humanoid robots was to say that they wanted to use robots that could go the places designed for humans and and so that's why they used the human form and I think you know there's an argument there it is true that the human form has a lot of complexity to it because you have very complicated legs in the biped and they're supporting the weight of the body and the arms whereas the quadrupeds can spread all that out so I'm sympathetic to your question I don't really have an answer I can tell you that the public's reaction to a humanoid robot is off the scale compared to anything we've done with Quadra Petro BOTS for what that's worth so we always get a lot of viewership if we show a humanoid doing something but I think it's a question that we will keep addressing we are going to keep pushing on getting the humanoid to do more and more human-like things even though we probably won't commercialize them as soon as we commercialize the other stuff how do you specify goals and although you said earlier that it's expensive to do like simulations and stuff do you have any intentions of doing any deep reinforcement learning what was the last thing I do you have any intentions of doing deep reinforcement learning I'll do the last one first we I'm sure we will use learning before too long I'm not sure whether it'll be deep reinforcement learning or something else but mostly we're interested in optimizing the complicated state space partitioning we do right now we use you know people make very simple decisions as to how to divide up the space and we think that these things could probably be really improved if we use the learning approach so that's probably the first place we will apply it we do a little bit of learning here and there but not much compared to how much learning is talking about out there what was the other question how do we specify a goal you mean to the robot or how do we decide as a company so I don't think there's any across-the-board answer we write applications for instant for each of these uses so for instance in the where we were doing the patrol route we have an application that has a UI that lets the user you know tell it the information it needs it can tell it to go ahead and start on the patrol and things like that for for the door I think I think there's a button on the on the controller we can show you afterwards if you want and you walk the robot up to the door were you steering it and then you press the button and then it starts looking for the door handle and it goes through the hole you know goes through the door but I don't think these answers are fundamental I think you could do it lots of different ways you know we're working on all the machinery coming up from the bottom to be able to do these things and then you know in some case you could have it be buttons on an 8 on a UI it could be an API that's accessed through some higher-level ai and we just aren't sweating that part of it at this point hi so aside from locomotion I can use my body for like you know nonverbal communication to communicate my intentions and and other such things even though I'm not always aware of it and I guess I'm wondering if this is something that you've considered for these robots I think the closest we've come is having the robot go like this after the flip which was a way of communicating we really haven't been anything along those lines I'll bet you though the people writing code can interpret a lot of the subtleties of what's you know what's working and what isn't by looking at things like that but the robot isn't trying to communicate that way I have two questions um how do you make the robots really how do you make the robots really fast how do we make them fast no my question is how did you make them fast I mean like the time how we get a lot of people who are really smart and good at working together with each other at our lab and then they make plans and we everybody tries to stay on the plan and then you know pull it together sometimes it doesn't go as fast as we like especially if we have to buy parts from someone else and they're slow that happens a lot no honestly is that what you mean so we don't make them that fast you know we're pretty fast you know usually four or five months to build a new robot something like that but mostly it's getting people to work together what's it what's the other question dad that question is why do the people push the robots why did it why do they push why do they push we're trying the robots are always balancing them themselves and so we want to show that they're that they can balance by by showing that when you knock them they still they don't fall over they stay up on their feet so we're kind of showing off are you building anything why not I don't know you should um let's way off why way off where is the base I'm not good at building no yes yes you are you might think you're not well some games there are you had to give it a try and you're the right a you're the right age to get started I'm six and a half perfect [Applause] would that I think please give the mark a big hand thank you very much [Applause]

Channel: Lex Fridman

Views: 82,619

Keywords: mit, agi, artificial intelligence, robotics, boston dynamics, atlas, spot, spotmini, computer vision, machine learning, marc raibert, ceo, ai safety, walking robot, humanoid robots, boston dynamics atlas, legged locomotion, deep learning, ai podcast, joe rogan

Id: LiNSPRKHyvo

Length: 53min 16sec (3196 seconds)

Published: Mon Apr 02 2018