Rodney Brooks: Robotics | Lex Fridman Podcast #217

1. 0:00 – 1:31

   Introduction

   1. LFLex Fridman0:00

      The following is a conversation with Rodney Brooks, one of the greatest roboticists in history. He led the Computer Science and Artificial Intelligence Laboratory at MIT, then co-founded iRobot, which is one of the most successful robotics companies ever. Then, he co-founded Rethink Robotics that created some amazing collaborative robots, like Baxter and Sawyer. Finally, he co-founded Robust.AI, whose mission is to teach robots common sense, which is a lot harder than it sounds. To support this podcast, please check out our sponsors in the description. As a side note, let me say that Rodney is someone I've looked up to for many years in my now over two decade journey in robotics because, one, he's a legit great engineer of real world systems, and two, he's not afraid to state controversial opinions that challenge the way we see the AI world. But of course, while I agree with him on some of his critical views of AI, I don't agree with some others, and he's fully supportive of such disagreement. Nobody ever built anything great by being fully agreeable. There's always respect and love behind our interactions, and when a conversation is recorded like it was for this podcast, I think a little bit of disagreement is fun. This is the Lex Fridman Podcast, and here is my conversation with Rodney Brooks.

2. 1:31 – 22:56

   First robots

   1. LFLex Fridman1:31

      What is the most amazing or beautiful robot that you've ever had the chance to work with?

   2. RBRodney Brooks1:37

      I think it was DOMO, um, which was made by one of my grad students, Aaron Edsinger. It now sits in, uh, Daniela Rus' office, uh, director of CSAIL, and it was just a beautiful robot. And Aaron was really clever. He didn't give me a budget ahead of time. He didn't tell me what he was gonna do. He just started spending money.

   3. LFLex Fridman1:58

      (laughs)

   4. RBRodney Brooks1:58

      He spent a lot of money.

   5. LFLex Fridman1:59

      Yeah.

   6. RBRodney Brooks2:00

      He and Jeff Weber, who, um, is a mechanical engineer, who Aaron insisted he bring with him when he became a grad student-

   7. LFLex Fridman2:07

      Mm-hmm.

   8. RBRodney Brooks2:07

      ... built this beautiful, gorgeous robot, DOMO, which is a to- upper torso, humanoid, two, two arms, uh, uh-

   9. LFLex Fridman2:16

      With fingers?

   10. RBRodney Brooks2:16

       ... three-fingered hands-

   11. LFLex Fridman2:17

       Mm.

   12. RBRodney Brooks2:17

       ... um, uh, and, um, a face, eyeballs, um, all, uh, not the, not the eyeballs, but everything else, series elastic actuators, uh, you can interact with it, um, cable driven, all the motors are inside, and it's just gorgeous.

   13. LFLex Fridman2:34

       The eyeballs are actuated too or no?

   14. RBRodney Brooks2:35

       Oh yeah, the eyeballs are actuated with cameras, and, you know, so it had a visual attention mechanism, you know-

   15. LFLex Fridman2:40

       Wow.

   16. RBRodney Brooks2:41

       ... looking when people came in and looking at their face and talking with them. Yeah.

   17. LFLex Fridman2:46

       Why was it amazing?

   18. RBRodney Brooks2:48

       The beauty of it. You said bea- but you said what was the most beau-

   19. LFLex Fridman2:50

       I said beauty. What is the most beautiful?

   20. RBRodney Brooks2:52

       It's just mechanically gorgeous, as, as everything Aaron builds has always been mechanically gorgeous. It's just exquisite in the detail.

   21. LFLex Fridman3:00

       Uh, we're talking about mechanically, like, literally the amount of actuators, the, uh-

   22. RBRodney Brooks3:04

       The actuators, the cables, he, um, anodizes different parts different colors, and it just looks like a work of art.

   23. LFLex Fridman3:13

       What about the face? Is it, do you find the face beautiful in robots?

   24. RBRodney Brooks3:17

       Um, when you make a, a robot, uh, it's making a promise for how well it will be able, able to interact, so I always encourage my students not to overpromise, you know, and-

   25. LFLex Fridman3:27

       Like, even with its essence, like, the w- the thing it presents, it should not overpromise?

   26. RBRodney Brooks3:32

       Yeah, so I... The, the joke I make, which I think you'll get, is if your robot looks like Albert Einstein, it should be as smart as Albert Einstein.

   27. LFLex Fridman3:39

       Yeah.

   28. RBRodney Brooks3:39

       So, uh, the, the only thing in, in DOMO's face is, uh, the eyeballs, um, and 'cause that's all it can do. It can look at you and pay attention, um, and so there is no f- it's not like one of those, um, Japanese robots that looks exactly like a person at all.

   29. LFLex Fridman3:59

       But see, the thing is, us humans, and dogs too, don't just use eyes for, as attentional mechanisms. They also use it to communicate. It's part of the communication. Like a dog can look at you, look at another thing, and look back at you, and that designates that we're going to be looking at that thing together.

   30. RBRodney Brooks4:16

       Yeah, or, or intent, you know?
3. 22:56 – 55:45

   Brains and computers

   1. RBRodney Brooks22:56

   2. LFLex Fridman22:56

      (laughs) So, uh, s- you're saying that there is a gap between the computer or the, the, um, the machine that performs computation, and this machine that appears to have consciousness and intelligence?

   3. RBRodney Brooks23:13

      Yeah.

   4. LFLex Fridman23:14

      Can we, um-

   5. RBRodney Brooks23:14

      That piece of meat in your head.

   6. LFLex Fridman23:16

      Piece of meat.

   7. RBRodney Brooks23:16

      And maybe it's not just the, the meat in your head, it's the rest of you, too. I mean, you have, you have, you actually have a neural system in your gut, um.

   8. LFLex Fridman23:25

      I, I tend to also believe... Not believe, but we're now dancing around things we don't know. But I tend to believe other humans are important. Like, so, we are almost like... I, I, I just don't think we would ever have achieved the level of intelligence we have without other humans. Uh, uh, I'm not saying so confidently, but I have an intuition that some of the intelligence is in the interaction.

   9. RBRodney Brooks23:51

      Yeah, and, and I think, uh, you know, I think it, uh, it seems to be very likely, again, we- you know, this is speculation, but we, our species and probably, um, probably Neanderthals to some extent, because you can find, uh, old bones where they seem to be counting on them by putting notches, um, that were Neothan- that Nean- Neanderthals had done. We are able to put, um, some of our stuff outside our body into the world.... and then other people can share it.

   10. LFLex Fridman24:20

       Mm-hmm.

   11. RBRodney Brooks24:20

       And then we get these tools that become shared tools. And so there's a whole coupling that would not occur in, you know, the single deep learning network which was fed, you know, all of the literature or something.

   12. LFLex Fridman24:33

       (laughs) Yeah. The, the, the neural network can't, um, step outside of itself. But is there, is there some, um ... Can we explore this dark room, uh, a little bit and try to get at something? Wh- wh- what is the magic? Where does the magic come from in the human brain that creates the mind? What, what, what's your sense as, as scientists that try to, uh, understand it and try to build it? What are the directions that, um, if followed might be productive? Is it creative interactive robots? Is it creating large deep neural networks that, uh, do, like, self-supervised learning and just, like, will, will, will discover that when you make something large enough some interesting things will emerge? Is it through physics and chemistry and biology, like artificial life angle? Like, we'll sneak up in this, uh, four quadrant matrix that you mentioned. Is there anything y- you're most-

   13. RBRodney Brooks25:31

       Yeah.

   14. LFLex Fridman25:31

       ... if you had to bet all your money (laughs) -

   15. RBRodney Brooks25:33

       (laughs) .

   16. LFLex Fridman25:33

       ... financial advice-

   17. RBRodney Brooks25:34

       I wouldn't.

   18. LFLex Fridman25:35

       (laughs) Okay.

   19. RBRodney Brooks25:36

       So, every intelligence we know, and that includes, you know, animal intelligence, dog intelligence, you know, um, um, octopus intelligence, which is a very different sort of architecture from, from us. Um, all the intelligences we know, um, perceive the world in some way, um, and then have action in the world, but they're able to, um, perceive objects in a way which is actually pretty damn phenom- phenomenal (laughs) and surprising. You know, we tend to think, you know, that, um, that, that, uh, the box over here between us, which is a sound box I think-

   20. LFLex Fridman26:21

       Mm-hmm.

   21. RBRodney Brooks26:21

       ... is what, is a blue box. But blueness, um, is something that we construct with, with, um, um, well, uh, color constancy. It's not a, it's not a, it's not... The blueness is not a direct function of the photons we're receiving, it's actually context, you know, which is why, um, y- you can turn, uh, you know, you, you maybe seen the examples where, um, someone turns a stop sign into a, um, some other sort of sign by just putting a couple of marks on them-

   22. LFLex Fridman26:53

       Mm-hmm.

   23. RBRodney Brooks26:53

       ... and the deep learning system gets it wrong. And everyone says, "But the stop sign's red. It, you know, why does it-"

   24. LFLex Fridman26:58

       Yeah.

   25. RBRodney Brooks26:58

       "... why does it think it's the other sort of sign?" Because redness is not intrinsic in just the photons, it's actually a construction of an understanding of the whole world and the relationship between objects to get con- color constancy. Um, but our, uh, tendency in order that we get an archive paper really quickly is you just show a lot of data and g- give-

   26. LFLex Fridman27:17

       Yeah.

   27. RBRodney Brooks27:17

       ... the labels and hope it figures it out. But it's not figuring it out in the same way we do. We have a very complex perceptual understanding of the world. Dogs have a very different perceptual understanding based on smell. They go smell, smell a post, they can tell, um, how many, y- you know, different dogs have visited it in the last 10 hours and how long ago. There's all sorts of stuff that we just don't perceive about the world. And just taking a single snapshot is not perceiving about the world. It's not perceiving the, the registration between us and the object. And registration is a, a philosophical concept. Brian Cantwell Smith talks about it a lot, very difficult squirmy thing to understand.

   28. LFLex Fridman27:59

       Mm-hmm.

   29. RBRodney Brooks27:59

       But I think none of our systems do that. We've always talked ab- in AI about the symbol grounding problem, how symbols that we talk about are grounded in the world.

   30. LFLex Fridman28:07

       Mm-hmm.
4. 55:45 – 1:15:55

   Self-driving cars

   1. LFLex Fridman55:45

      into it. Speaking of robots that operate in the real world, let's talk about self-driving cars.

   2. RBRodney Brooks55:53

      Oh. (laughs)

   3. LFLex Fridman55:54

      (laughs) Okay. Because you do, you have built robotics companies. You're- you're one of the greatest roboticists in history and that's not in space of i- just in the space of ideas, we'll also probably talk about that, but in the actual building and execution of businesses that make robots that are useful for people and that actually work in the real world and make money. You also sometimes are critical of Mr. Elon Musk, or let's more specifically focus on this particular technology which is autopilot inside Teslas. What are your thoughts about Tesla autopilot or more generally vision-based machine learning approach to semi-autonomous driving? Uh, th- these are robots that are being used in the real world by hundreds of thousands of people and, uh, w- if you want to go there I can go there but let's not too much, which they're, let's say they're on par safety-wise as humans currently, meaning human alone versus human plus robot.

   4. RBRodney Brooks56:58

      Okay. So first let me say I really like the car I came here- in here today.

   5. LFLex Fridman57:04

      Which is?

   6. RBRodney Brooks57:05

      Um, a 2021, um, model, uh, Mercedes E450.

   7. LFLex Fridman57:12

      Mm-hmm.

   8. RBRodney Brooks57:13

      I am impressed by the, um, m- machine vision. So are now other things. I'm impressed by what it can do. I'm really impressed, um, with, uh, many aspects of it. And- and I'm, um ...

   9. LFLex Fridman57:29

      It's able to stay in lane? Is it, uh-

   10. RBRodney Brooks57:31

       Oh yeah, it does the- it does the lane stuff. Um, it, uh, uh, you know, it- it's- it's looking at- uh, I mean the side of me, it's telling me about nearby cars.

   11. LFLex Fridman57:40

       For blind spots and so on?

   12. RBRodney Brooks57:41

       Yeah. When I- when I- when I- when I'm going in close to something to park, I get this beautiful, gorgeous, top-down view of the world. I am impressed up the wazoo of how, you know, registered and m- metrical that is.

   13. LFLex Fridman57:56

       Oh, so it's like multiple cameras and it's all very connected together-

   14. RBRodney Brooks57:59

       Yeah, uh, uh-

   15. LFLex Fridman57:59

       ... to produce the 360 view kind of thing?

   16. RBRodney Brooks58:01

       360 view, uh, you know, it's synthesized ...

   17. LFLex Fridman58:03

       Okay.

   18. RBRodney Brooks58:03

       ... so it's above the car. And it is unbelievable. I- I got this car in January. It's the longest I've ever owned a car without digging it. Um, so it's better than me. It- it-

   19. LFLex Fridman58:13

       Wow, okay.

   20. RBRodney Brooks58:13

       ... or me and it together, uh, are better. So I'm not saying technology's, um, uh, bad or not useful, but here's my point.

   21. LFLex Fridman58:25

       Yes.

   22. RBRodney Brooks58:27

       It's just, it's a replay of the same movie.

   23. LFLex Fridman58:30

       Mm-hmm.

   24. RBRodney Brooks58:31

       Okay? So maybe you've seen me ask this question before, but, um, when, um, when- when did the first car go over 55 miles an hour for over, um, over 10 miles on a public freeway with other traffic around driving completely autonomously? When did that happen?

   25. LFLex Fridman58:59

       The- is it- was it CMU in the '80s or something? I- it was a long time ago.

   26. RBRodney Brooks59:02

       It was actually 1987 in- in Munich. Um ...

   27. LFLex Fridman59:05

       Oh, Munich, yeah, yeah.

   28. RBRodney Brooks59:06

       Uh, at the Bundeswehr.

   29. LFLex Fridman59:07

       Yes.

   30. RBRodney Brooks59:08

       Um, um, um ... So they- they had it running in 1987. When do you think, and Elon has said he's gonna do this, when do you think we'll have the first car drive coast to coast in the US hands off the wheel, hands off the wheel, feet off the pedals coast to coast?
5. 1:15:55 – 1:26:45

   Believing in the impossible

   1. LFLex Fridman1:15:55

      y- you have a harshness to you sometimes in your criticisms of what is crit-

   2. RBRodney Brooks1:16:01

      What? (laughs)

   3. LFLex Fridman1:16:01

      See? (laughs) .

   4. RBRodney Brooks1:16:03

      (laughs)

   5. LFLex Fridman1:16:03

      That's hype. (laughs)

   6. RBRodney Brooks1:16:04

      (laughs)

   7. LFLex Fridman1:16:05

      Uh, a- and so like, c- 'cause people extrapolate, like you said, and they, they kind of buy into the hype and then they, th- they kind of start to think that, um, uh, the, the technology's way better than it is. But let me ask you maybe a difficult question.

   8. RBRodney Brooks1:16:23

      Sure.

   9. LFLex Fridman1:16:25

      D- do you think, if you look at history of progress, don't you think to achieve the, quote, "impossible," you have to believe that it's possible?

   10. RBRodney Brooks1:16:34

       Oh, abso- absolutely. Yeah. Look, look, his, his, his, his, his two great runs, great, unbelievable, 1903, first human, um, pow- y- human, um, you know, heavier than air flight.

   11. LFLex Fridman1:16:49

       Yeah.

   12. RBRodney Brooks1:16:50

       1969, we land on the moon.

   13. LFLex Fridman1:16:52

       Yeah.

   14. RBRodney Brooks1:16:52

       That's 66 years. I'm 66 years old.

   15. LFLex Fridman1:16:55

       Yeah.

   16. RBRodney Brooks1:16:55

       In my lifetime, that span of my lifetime-

   17. LFLex Fridman1:16:58

       Yeah.

   18. RBRodney Brooks1:16:58

       ...we went from barely g- you know, flying, I don't know what it was, 50 feet-

   19. LFLex Fridman1:17:02

       Yeah.

   20. RBRodney Brooks1:17:02

       ...or the length of the first flight or something, to landing on the moon. Unbelievable.

   21. LFLex Fridman1:17:08

       Yeah.

   22. RBRodney Brooks1:17:08

       Fantastic.

   23. LFLex Fridman1:17:09

       But that requires, by the way, one of the Wright brothers, both of them, but one of them didn't believe it's even possible like a year before. Right? So the, like, not just possible soon, but like-

   24. RBRodney Brooks1:17:20

       Yeah.

   25. LFLex Fridman1:17:20

       ...ever.

   26. RBRodney Brooks1:17:21

       So, so, so, so, you know-

   27. LFLex Fridman1:17:22

       How important is it to believe and be optimistic is what I guess I'm asking?

   28. RBRodney Brooks1:17:25

       Oh yeah, it is important. It's when it goes craz- when, when, when I, you know, you said, uh, what, what did, what was the word you used for my bad...

   29. LFLex Fridman1:17:34

       Harshness?

   30. RBRodney Brooks1:17:34

       Harshness, yes. (laughs)

Episode duration: 2:24:51