YouSaid · the spoken record

Rodney Brooks

lines on the record: 146
first: 2021-09-03
most recent: 2021-09-03
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“Yeah, until it's possible, but I, you know. I'll be incredibly surprised if that happens. I'll also be incredibly surprised that after all the decades that I've been doing this, where every few years someone thinks, now we've got it. Now we've got it. Four or five years ago I was saying, I don't think we've got it yet. And everyone was saying, you don't understand how powerful AI is. I had people tell me, you don't understand how powerful it is. I sort of had a track record of what Think, well, this is no different from before, or we had bigger computers. We had bigger computers in the 90s, and we could do more stuff.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Whatever it is, but there's also a mechanism that's been built up. It's not just. Random search that mechanism prunes it. Dramatically.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Anyway, the point is, you know, this idea that you just let reinforcement learning figure everything out is so counter to how a kid does stuff. So again, story about my grandson. I gave him this box that had lots of different lock mechanisms. He didn't ran them, you know, and he was eighteen months old. He didn't randomly try to touch every surface or push everything. He found he could see where the mechanism was, and he started exploring the mechanism for each of these different lock mechanisms. And there was reinforcement, no doubt, of some sort going on there. But he applied a pre-filter which cut down the search space dramatically.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's in the next room. These robots are just bashing around to try and use reinforcement learning to learn how to act. Can I go see them? Oh, no, they're secret. They were my robots that were secret.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“In a conference room, bad conference room with some of the people. And they tell me about their reinforcement learning experiment with robots, which are just trying stuff out. And then my robots, they're Sawyers that we sold them. And they really like them because Sawyers are compliant and consents forces, so they don't break when they're bashing into walls. They stop and all this stuff. And, you know, so you just let the robot do stuff and eventually it figures stuff out.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“There's a great counter to reinforcement learning. We'll just give the robot plenty of time to try everything. Can I tell a little side story here? So I'm in Deep Mind in London. This is three, four years ago, where there's a big Google building and then you go inside and you go through this more security and then you get to DeepMind where the other Google employees can't go. And I'm”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, let's talk about manipulation for a second because I had this really blinding moment. You know, I'm a grandfather, so grandfathers had blinding moments. Three or four miles from here last year, my 16 month-old grandson was in his new house for the first time, right? First time in this house. And he'd never been able to get to a window before, but this had some low windows. And he goes up to this window with a handle on it that he's never seen before. And he's got one hand pushing the window and the other hand turning the handle to open the window. He knew two different hands, two different things he knew how to put together. And he's sixteen months old”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“I sort of think all of them There are no easy paths to do well. We sort of go reductionist and we reduce it. If only we had all the location of all the points in 3D. Things would be great. If only we had labels on the images, things would be great. But, you know, as we see, that's not good enough. Some deeper understanding.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Don't view it as a paradox. What did evolution spend its time on? Spend its time on getting us to perceive and move in the world. That was $600 million as multi-cell creatures doing that. And then it was relatively recent that we were able to hunt or gather or even animals hunting. That's much more recent. And then anything that we speech language, those things are a couple of hundred thousand years probably if that long. And then agriculture, 10,000 years. All that stuff was built on top of those earlier things, which took a long time to develop.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“But I think we jumped between what we're capable of and how we're doing it right there. A little confusion that went on As we're telling each other stories.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Until we got computers, so we're better at it than people. And then we realized, you know, if you go back to the 90s, you'll see the stories in the press around when Kasparov was beaten by Deep Blue. Oh, this is the end of all sorts of things. Computers are going to be able to do anything from now on. And we saw exactly the same stories with Alpha Zero, the Go playing program.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Let me give us sort of a Another story. You go back to the original teams working on AI. From the late 50s into the 60s, and you go to the AI lab at MIT. Who was it that was doing that? Was it a bunch of really smart kids who got into MIT? They were intelligent. So, what's intelligence about? Well, the stuff they were good at playing chess, doing integrals, that was hard stuff. You know, a baby could see stuff. I wasn't intelligent. Anyone could do that. That's not intelligence. And so there was this intuition that the hard stuff is the things they were good at and the easy stuff was the stuff that everyone could do. Maybe I'm overplaying it a little bit, but I think there's an element of that.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Squammy thing to understand. But I think none of our systems do that. We've always talked in AI about the symbol grounding problem, how our symbols that we talk about are grounded in the world. And when deep learning came along and started labeling images, people said, ah, the grounding problem has been solved. No, the labeling problem was solved with some percentage accuracy, which is different from the grounding problem.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Construction of an understanding of the whole world and the relationship between objects, the color constancy. But our tendency in order that we get an archive paper really quickly is you just show a lot of data and give 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 perceptional understanding based on smell. They go smell a post. They can tell how many 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 registration between us and the object. And registration is a philosophical concept Brian Cantwell-Smith talks about a lot very difficult.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Can turn, you know, you've maybe seen the examples where someone turns a stop sign into some other sort of sign by just putting a couple of marks on them and the deep learning system gets it wrong and everyone says, but the stop sign's red. Why is it think it's the other sort of sign? Because redness is not intrinsic in just the photons. It's actually...”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“So every intelligence we know, and includes animal intelligence, dog intelligence, octopus intelligence, which is a very different sort of architecture from us, all the intelligences we know perceive the world in some way and then have action in the world. But they're able to perceive objects in a way which is actually pretty damn phenomenal and surprising. You know, we tend to think that the box over here between us, which is a sound box, I think. It's a blue box. But blueness is something that we construct with color constancy. The blueness is not a direct function of the photons we're receiving. It's actually context, which is why...”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, and I think it seems to me very likely, again, this is speculation, but our species, and probably in the end, those to some extent, because you can find old bones where they seem to be counting on them by putting notches that were Neanderthals. We are able to put some of our stuff outside our body into the world, and then other people can share it. And then we get these tools that become shared tools. And so there's a whole coupling that would not occur in the single deep learning network, which was fed all of literature or something.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Maybe it's not just the meat in your head, it's the rest of you too. I mean, you actually have a neural system in your gut”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Computation is sort of a thing that's become dominant as a metaphor. Is it the right metaphor? All three of these four fields adopted computation and a lot of it swirls around Warren McCulloch and all his students and he funded a lot of people. And our human metaphors, our limitations to human thinking. Into this. The three themes of the I have a little to say about computation.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“That's my argument in this book. Now, and people say, well, what is it then? And they say, well, I wish I knew that, write the book about that. But give some ideas. So there's three things. Computation is sort of a particular thing we use. Oh, can I tell you one beautiful thing? I used an example of a thing that's different from computation. You hit a drum and it vibrates. And there are some stationary points on the drum surface because the waves are going up and down as stationary points. You could compute them to arbitrary precision, but the drum just knows them. The drum doesn't have to compute. What was the very first computer program ever written by Ada Lovelace to compute Bernoulli numbers? And Bernoulli numbers are exactly what you need to find those stable points in the drum surface. And there was a bug in the program.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“I suspect that 100 years or 200 years from now, neither quantum mechanics nor dark matter will be talked about in the same terms, in the same way that Floggeson's theory eventually went away because it just wasn't an adequate explanatory metaphor. That metaphor was the stuff in the burning, the burning is in the matter. Turns out the burning was outside the manor. It was the oxygen.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's this metaphor of place and container, which is a combination of our place cells in our hippocampus and our cortex. But this is how we use metaphors for mostly to think about. And when we get outside of our metaphor range, we have to invent tools which we can sort of switch on to use. So calculus is an example of a tool. It can do stuff that our raw reasoning can't do. And we've got conventions of when you can use it or not. But sometimes, you know, people try to, or all the time, we always try to get physical metaphors for things, which is why quantum mechanics has been such a problem for a hundred years, because it's a particle. No, it's a wave. It's got to be something we understand. And I say, no, it's some weird mathematical object that's different from those. But we want that metaphor. Well, you know.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“It's gotten But computation in the way Turing thinks about it and the way most people think about it actually fits very well with thinking like a hunter-gatherer. Places and there can be stuff in places, and the stuff in places can change, and it stays there until someone changes it.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“They're all going around at the same time. And three of these four disciplines turn to computation as their primary metaphor. So I've got a couple of chapters in the book. One is titled Wait. Computers are people because that's where our computers came from. From people who were computing stuff. And then I've got another chapter, wait, people are computers, which is about computational neurosci So there's this whole circle here. That computation is it. And I have talked to people about, well, maybe it's not computation that goes on in the head. Of course it is. Okay When Elon Musk's rocket goes up, is it computing? Is that how it gets into orbit by computing? But we've got this idea if you want to build an AI system, you write a computer program.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, McCulloch and Pitts was much younger than him in 1943, had written a paper inspired by Bertrand Russell on a calculus for the ideas imminent in neural systems. They had tried to without any real proof. Had tried to give a formalism for neurons. Basically, in terms of logic, AND gates or gates and nut gates with no real evidence that that was what was going on, but they talked about it, and that was picked up by Minsky for his 1953 dissertation, which was a neural network, we would call it today. It was picked up by John von Neumann when he was designing the EdBack computer in 1945. He talked about its components being neurons. based on, and it references, he's only got three references and one of them is the McCulloch Pitts paper.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Was neuroscience before, but it wasn't a Of neuroscience. It was these ganglia and there's electrical charges, but no one knows what to do with it. And furthermore, there were a lot of players who are common across them. I've identified common players except for artificial intelligence and abiogenesis. I don't have. But for any other pair, I can point to people who work. And a whole bunch of them, by the way, were at the research lab for electronics at MIT, where Warren McCulloch held forth. In fact, McCulloch's Letvin and Matchurana wrote the first paper on functional neuroscience called What the Frog's Eye Tells the Frog's Brain, where instead of it just being this bunch of nerves, they sort of showed what different Anatomical components were doing and telling other anatomical components and generating behavior in the front.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“The top row is neuroscience and abiogenesis. How does living matter? How does non-living matter become living matter? Disciplines. These four disciplines all Into the current form in the period 1945 to 1965.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's modeled after humans, how humans do stuff. And I think Turing says in the 36 paper, one of the critical facts here is that a human has a limited amount of memory. So that's what we're going to put onto our mechanical computers. So, you know, unlike... Like mass or charge, or It's not given by the universe. This is what we're going to call computation. And then it has this really, you know, it had this really good implementation, which has completely changed our technological world. That's computation. Second part of the book, or argument in the book, I have this two by two matrix with science in the top row, engineering in the bottom row, left column is intelligence, right column is life. So, in the bottom row, the engineering, there's artificial intelligence, and there's artificial life.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Was a step which required knowing whether Fermat's last theorem was true or not because it was not known at the time. And that's too much trouble for a person to do as a step. And Hubcraft and Norman sort of said a similar thing later that year. And by 1975 in the AHO Hopcroft, the Norman book, they're saying, well, you know, we don't really know what computation is, but intuition says this is sort of about right, and this is what it is. That's computation. It's a sort of Agreed upon thing which happens to be really easy to implement in silicon. And then we had Moore's law, which took off and it's been an incredibly powerful tool. I certainly wouldn't argue with that. The version we have of computation, incredibly powerful.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“And Donald Knuth in his first volume of his Art of Computer Programming in around 1968 says, well, what's computation? It's this stuff lecturing says that a person could do each step without too much trouble. And so, one of his examples of what would be too much trouble.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“And there he said, and he says in the paper, I don't have any real arguments for this, but based on intuition. So that's how he defined computation. And then if you look over the next, from 1936 up until really around 1975, you see people struggling with... Is this really what computation is? And so Marvin Minsky, very well known in AI, but also a fantastic mathematician in his book Finite Infant Machines from the mid-60s, which is a beautiful, beautiful mathematical book, says at the start of the book, well, what is computation? Turing says it's this. And yeah, I sort of think it's that. It doesn't really matter whether stuff's made of wood or plastic. It's just, you know, relatively cheap stuff can do this stuff. And so yeah, it seems like computation.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Came with a set of instructions that as a person could do with pencil and paper, write down things on the tape and erase them and put new things there. And he was able to show that that system was not able to do something that Hilbert had hypothesized. So he disproved it. But he had to show that this system was good enough to do whatever could be done, but couldn't do this other thing.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Because that was a mechanical process that people use to generate tables. They were called computers, the people at the time. And they followed a set of rules where they had paper and they would write numbers down and based on the numbers, they'd keep writing other numbers. And they would produce numbers for these tables, engineering tables that the more iterations they did, the more significant digits came out. And so Turing in that paper set out to define what sort of machine could do that mechanical machine. It can produce an arbitrary number of digits in the same way a human computer did. And he came up with a very simple Of constraints where there was an infinite supply of paper, the tape of the Turing machine, and each Turing machine had”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“An effective way of getting answers. And Hilbert really worked with rewriting rules, as did a church, who also, at the same time, a month earlier than Turing, disproved Hilbert's one of these three hypotheses. The other two had already been disproved by G ⁇ del. So Turing set out to disprove it because it's always easier to disprove these things than to prove that there is an answer. And so he needed, and it really came from his professor, I was an undergrad at Cambridge who said, who'd turned it into, is there a mechanical process? So he wanted to have a show a mechanical process that could Calculate numbers.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I believe that it's very wrong. In fact, I'm halfway through a, I think I'll be about a 480-page book titled, the working title is Not Even Wrong. If I may, I'll tell you a bit about that book There's three thrusts to it. One is the history of computation, what we call computation. All the way back to some manuscripts in Latin from 1614 and 1620 by Napier and Kepler through Babbage and Lovelace. Turing's 1936 paper is what we think of as the invention of modern computation. And that paper, by the way, did not set out to invent computation. It set out to negatively answer one of Hilbert's three later set of problems. He called it...”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Certainly, machines can think because I believe you're a machine and I'm a machine and I believe we both think. I think. I think any other philosophical position is sort of a little ludicrous, what does think mean if it's not something that we do? And we are machines. So yes, machines can, but do we have a clue how to build such machines? That's a very different question. Are we capable of building such machines? Are we smart enough? We think we're smart enough to do anything, but maybe we're not. Maybe we're just not smart enough to build stuff like us.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“No, actually, to be honest, I realized my limitation on building mechanical stuff. So I just built the brains mostly. Different technologies as I got older. I built a learning system which was chemical based and I had this IceCube tray. Each well was a cell and by applying voltage to the two electrodes it would build up a copper bridge so over time it would learn a simple network so I could teach it stuff and that was Mostly things were driven by my budget and nails as electrodes and ice cream, I mean an ice cube tray was about my budget at that stage. Later I managed to buy transistors and then I could build gates and flip-flops and stuff.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“They were some of the robots that they had were arms, you know, big arms to move nuclear material around, but they had pictures of welding robots that looked like humans under the sea welding stuff underwater. So they weren't real robots, but they were, you know, what people were thinking about for robots.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Got these, I was born in the end of 1954, and I grew up in Adelaide, South Australia, and I have these two books that are dated 1961. So I'm guessing my mother found them in a store in 62 or 63, how and why Wonder Books of Electricity and how and why Wonderbook of giant brains and robots. I learned how to build circuits when I was eight or nine, simple circuits and I learned the binary system and saw all these drawings mostly of robots. And then I tried to build them for the rest of my childhood.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Or intent on both Baxter and Sawyer at Rethink Robotics, they had a screen with graphic eyes so it wasn't actually where the cameras were pointing, but the eyes would look in the direction it was about to move its arm. So people in the factory nearby were not surprised by its motions because it gave that intent away.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“So the joke I make, which I think you'll get, is if your robot looks like Albert Einstein, it should be the smartest Albert Einstein. So the only thing in Domo's face is the eyeballs because that's all it can do. It can look at you and pay attention. And so there is no, it's not like one of those Japanese robots that looks exactly like a person at all.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“When you make a robot, it's making a promise for how well it will be able to interact. So I always encourage my students not to overpromise.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Just mechanically gorgeous as everything Aaron builds has always been mechanically gorgeous, it's just exquisite in the detail.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“The eyeballs are actuated with cameras, and you know, so had a visual attention mechanism. Looking when people came in and looking in their face and talking with them.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“Three fingered hands and face eyeballs. Not the eyeballs, but everything else, series elastic actuators, you can interact with it. Cable driven, all the motors are inside, and it's just gorgeous.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source
“It was Domo, which was made by one of my grad students, Aaron Ed Singer. It now sits in Daniela Russe's office, director of CSAL. 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 going to do. He just started spending money. He and Jeff Weber, who is mechanical engineer who Aaron insisted he bring with him when he became a grad student, built this beautiful, gorgeous robot domo, which is upper torso humanoid, two arms.”
2021-09-03 · Lex Fridman Podcast · #217 – Rodney Brooks: Robotics · IDENTIFIED FROM THE TRANSCRIPT · source