YouSaid · the spoken record

Jeff Hawkins

lines on the record: 180
first: 2021-08-08
most recent: 2021-08-08
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

“I think intelligent machine could be conscious, but that does not again imply any of these desires and goals that you're worried about. We can talk about what it means for machine to be conscious.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, in terms of if you build the new Cortex equivalent, it will not have any of these desires or emotional states. Now, you can argue that that neocortex won't be useful unless I give it some agency, unless I give it some desire, unless I give it some motivation. Otherwise, you'll be as lazy and do nothing. You could argue that. But on its own, it's not going to do those things. This is not going to sit there and say, I understand the world. Therefore, I care to live. No, it's not going to do that. It's just going to say, I understand the world.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Where does your desire to live come from? It's an old evolutionary design. I mean, we could argue, does it really matter if we live or not? Objectively no, right? We're all going to die eventually. Evolution makes us want to live. Evolution makes us want to fight to live. Evolutionists want to care and love one another and to care for our children and our relatives and our family and so on. And those are all good things. But they come about not because we're smart, because we're animals that grew up. The hummingbird in my backyard cares about its offspring. Every living thing in some sense cares about surviving. When we talk about creating intelligent machines, we're not creating life. We're not creating evolving creatures. We're not creating living things. We're just creating a machine that can learn really sophisticated stuff. And that machine, it may even be able to talk to us.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't think so. I think. Tempting to think that way. First of all, I don't think anyone, hardly anyone thinks that's for computers today. No one says, oh, this thing needs to write. I shouldn't be able to turn it off. Or, you know, if I throw it in the trash can and hit it with a sledgehammer, for my criminal act, no, no one thinks that. And now we think about intelligent machines, which is where you're going. And all of a sudden, like, well, now we can't do that. I think the basic problem we have here is that people think intelligent machines will be like us. They're going to have the same emotions as we do, the same feelings as we do. What if I can build an intelligent machine that absolutely could care less about whether it was on or off or destroyed or not? It just doesn't care. It's just like a map. It's just a modeling system. It has no desires to live nothing.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Don't know. I'm not sure. I think that's the right question. Let's look at computers as an analogy. Computers are a million times faster than us. They do things we can't understand. Most people have no idea what's going on when they use computers. How we integrate them in our society? Well, we don't think of them as their own entity. They're not living things. We don't afford them rights. We rely on them, our survival as seven billion people or something like that is relying on computers now.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it's a lot of engineering problems. I don't think it's a fundamental problem I could ask you the same question How hard is for computers to fit into a human world?”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Computing has been in the last century by far. Because it's getting at a fundamental thing. It's not a vision system or a learning system. It's not a vision system or hearing system. It is a learning system. It's a fundamental principle how you learn the structure in the world, how you gain knowledge and be intelligent. And that's what the Thousand Brain says was going on. And we have a particular implementation in our head, but it doesn't have to be like that at all.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“And so in the future, to me, robotics and AI will merge. They're not going to be separate fields because the algorithms for really controlling robots are going to be the same algorithms we have in our brain algorithms. Today we're not there, but I think that's going to happen. And then, but not all AI systems will be robotics. You can have systems that have very different types of embodiments. Some will have physical movements, some will not have physical movements. It's a very generic learning system. Again, it's like computers. The Turing machine is like, it doesn't say how it's supposed to be implemented. It doesn't say how big it is. It doesn't tell you what you can apply it to, but it's a computational principle. Cortical column equivalent is a computational principle. It's about learning. It's about how you learn, and it can be applied to a gazillion things. This is what I think this impact of AI is going to be as large, if not larger than...”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“But in a very, very loose sense. It's like, again, learning is inherently about the sub-brewing the structure in the world and discover the structure of the world. You have to move through the world, even if it's a virtual world, even if it's a conceptual world. You have to move through it. It doesn't exist in one. It has some structure to it. So here's a couple of predictions of getting what you're talking about. In humans, the same algorithm does robotics, right? It moves my arms, my eyes, my body, right?”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay. The interactive. You can think of this cortical column as what we call a sensory motor learning system. It has the idea that there's a sensor and then it's moving. That sensor can be physical. It can be like my finger and it's moving in the world. It could be like my eye and it's physically moving. It can also be virtual. So it could be an example would be I could have a system that lives in the internet that samples information on the internet and moves by following links. That's a sensory motor system.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“It's the first two more than the third one, I would say. Again, let's just use computers as an analogy. The pioneers in computing, people like John Van Norman and Alan Turing, they created this thing we now call the universal Turing machine, which is a computer, right? Did they know how it was going to be applied? Where it was going to be used. Could they envision any of the future? No. They just said this is like a really interesting computational idea about algorithms and how you can implement them in a machine. And we're doing something similar to that today. We are building this sort of universal learning principle Can be applied to many, many different things.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Today we know enough to build this. Sitting here with, you know, I know the steps we have to go. There's still some engineering problems to solve, but we know enough. And this is not like, oh, this is an interesting idea. We have to go think about it for a few decades. No, we actually understand it pretty well in details. So not all the details, but most of them. So it's complicated, but it is an engineering problem. So in my company, we are working on that. We are basically the roadmap, how we do this. It's not going to take decades. It's a matter of a few years optimistically, but I think that's possible. Complex things if you understand them, you can build them.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, but then it just copied that. So, as I said earlier, figuring out how to model something like a space is really hard. And evolution had to go through a lot of tricks. And these cells I was talking about, these bridge cells and place cells, they're really complicated. This is not simple stuff. This neural tissue works on these really unexpected, weird mechanisms. But it did it. It figured it out. But now you could just make lots of copies of it.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“In the same mechanisms, yeah. It's a little bit like computers, right? All computers are universal Turing machines, even the little teeny one that my toaster and the big one that's running some cloud server someplace. They're all running on the same principle. They can apply different things. So the brain is all built on the same principle. It's all about learning these models, structured models using movement and reference frames. And it can be applied to something as simple as a water bottle and a coffee cup and it can be applied to thinking like what's the future of humanity and what? Why do you have a hedgehog on your desk? I don't know.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“It's very sophisticated. So the same mechanism that can model a water bottle or a coffee cup can model conceptual objects as well. That's the beauty of this discovery that this guy, Vernon Mountcastle made many, many years ago, which is that there's a single cortical algorithm underlying everything we're doing”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“So I wanted to get back to your point about hierarchical representation, the world itself is hierarchical, right? And I can take this microphone in front of me. I know inside there's going to be some electronics. I know there's going to be some wires and I know there's going to be a little diaphragm that moves back and forth. I don't see that, but I know it. So everything in the world is hierarchical. You just go into a room. It's composed of other components. The kitchen has a refrigerator. The refrigerator has a door. The door has a hinge. The hinge has screws and pin. So anyway, the modeling system that exists in every cortical column learns the hierarchical structure of objects. So it's a very sophisticated modeling system in this grain of rice. It's hard to imagine, but this grain of rice can do really sophisticated things. It's got 100,000 neurons in it.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“So is our physical objects. So take this water bottle. I'm not particular to this brand, but this is a Fiji water bottle. And it has a logo on it. I use this example in my book. Our company's coffee cup has a logo on it. But this object is hierarchical. It's got like a cylinder and a cap, but then has this logo on it. And the logo has a word. The word has letters. The letters have different features. So I don't have to remember, I don't have to think about this. So I say, oh, there's a Fiji logo on this water bottle. I don't have to go through and say, oh, what is a Fiji logo? It's the F and I and a J and I, and there's a hibiscus flower. And oh, it has the pest, you know, the stamen on it. I don't have to do that, I just incorporate all of that in some sort of hierarchical representation. I say, you know, put this logo on this water bott”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, whatever. But the point is, when we think about the world, when we have knowledge about the world, how is that knowledge organized, Lex? Where is it in your head? The answer is it's in reference frames. So the way I learn the structure of this water bottle where the features are relative to each other, when I think about history or democracy or mathematics, the same basic underlying structures happening. There's reference frames for where the knowledge that you're assigning things to. So in the book, I go through examples like mathematics and language and politics. But the evidence is very clear in the neuroscience. The same mechanism that we use to model this coffee cup we're going to use to model high-level thoughts. The demise of humanity, whatever you want to think about.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, first you apply it to where your finger is. So here's the way I think about it. The old part of the brain says, where's my body in this room? The new part of the brain says, Where's my finger relative to this object? Where is a section of I relative to this object? Where I'm looking at one little corner here, where is that relative to this patch of my retina? And then we take the same thing and apply it to concepts, mathematics, physics, you know, humanity, whatever you want to think. Adventure.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Then we said, well, how do neurons make reference frames? It's not obvious. You know, X, Y, Z coordinates don't exist in the brain. It's just not the way it works. So that's when we looked at the older part of the brain, the hippocampus and the Antoronto cortex, where we knew that in that part of the brain, there's a reference frame for a room or a reference frame for environment. Remember I talked earlier about how you could make a map of this room So we said, oh, they are implementing reference frames there. So we knew that reference frames needed to exist in every cortical column. And so that was a deductive thing. We just deduced it, has to exist.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Exactly relative to the coffee cup. And to do that, I have to have a reference frame for the coffee cup. It has to have a way of representing the location of my finger to the coffee cup. And then we realize, of course, every part of your skin has to have a reference frame relative to things as such. And then we did the same thing with vision. So the idea that a reference frame is necessary to make a prediction when you're touching something or when you're seeing something and you're moving your eyes or you're moving your fingers. It's just a requirement. To know what to predict if I have a structure, I'm going to make a prediction, I have to know where it is I'm looking or touching it.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Turns out for you to make a prediction, and I walk you through the thought experiment in the book where I was predicting what my finger was going to feel when I touched the coffee cup, was a ceramic coffee cup, but this one will do. And what I realized is that to make a prediction what my finger is going to feel, like I was guessing I feel different than this, what's it feel different if I touch the hole or this thing on the bottom, make that prediction. The cortex needs to know where the finger is, the tip of the finger. Relative to the coffee cup”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay, so again, a reference frame I mentioned earlier about a model of a house. And I said, if you're going to build a model of a house in a computer, they have a reference frame. And you can think of a reference frame like Cartesian coordinates, like X, Y, and Z axes. So I could say, oh, I'm going to design a house. I can say, well, the front door is at this location, X, Y, Z, and the roof is at this location, X, Y, Z, and so on. That's the type of reference frame.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“That's part of this theory. It's like saying, oh, it's a detail, but it was like a crack in the door. It was like, how do we get to figure out how these neurons do this? What is going on here? So we just looked at prediction as like, well, we know that's ubiquitous. We know that every part of the cortex is making predictions. Therefore, whatever the predictive system is, it's going to be everywhere. We know there's a gazillion predictions happening at once. So let's see if we can start teasing apart, you know, ask questions about how could neurons be making these predictions. sort of built up to now what we have this thousand brains theory, which is complex, you know, it's just I can state it simply, but we just didn't think of it. We had to get there step by step very, it took years to get there.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“And then there's a voting mechanism. Then there's a voting mechanism which you're conscious of, which leads to your singular perception. That's why you perceive something. So that's the thousand brain theory. The details are how we got to that theory are complicated. It wasn't we just thought of it one day. And one of those details is we had to ask how does a model make predictions? And we talked about just these predictive neurons.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“The thousand main theory says that basically every cortical column in your New York cortex is a complete modeling system. And that when I ask where I have a model of something like a coffee cup, it's not in one of those models, it's in thousands of those models. There's thousands of models of coffee cups. That's what the Thousand Brilliants...”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“And if someone says get ready set, you get up and you're ready to go. And then when you restart, you get a little bit earlier start. So that ready set is like the prediction. And the neuron's like ready to go quicker. And what happens is when you have a whole bunch of neurons together and they're all getting these inputs, the ones that are in the predictive state, the ones that are anticipating to become active. If they do become active, they happen sooner. They disable everything else. And it leads to different representations in the brain. So you have to It's not isolated just to the neuron. The prediction occurs when the neuron, but the network behavior changes. So what happens under different predictions, different inputs have different representations. So how I predict is going to be different under different contexts, what my input will be is different under different contexts. So this is a key little theory how this works.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Oh, yeah, yeah, yeah. So having a prediction side of individual neuron is not that useful. So what? The way it manifests itself in neural tissue is that A neuron emits these spikes or a very singular type of event. If a neuron is predicting that it's going to be active, it emits its spike very, a little bit sooner, just a few milliseconds sooner than it would have otherwise. It's like I give the analogy in the book as like a sprinter on a starting blocks in a race.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“The neuron is saying, I expect that I might become active shortly. And that internal, so the internal spike is a way of saying you might be generating external spike soon. I predicted you're going to become active. And we wrote a paper 2016 which explained how this manifests itself in neural tissue and how it is that this all works together. We think there's a lot of evidence supporting it. So that's where we think that most of these predictions are internal. That's why you can't internal and neuron you can't perceive them.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Making so many of them, which we're totally unaware of, just the vast majority have no idea that you're doing this. We were trying to figure out how could this be? Where are these happening? I won't walk you through the whole story unless you insist upon it, but we came to the realization that most of your predictions are occurring inside individual neurons, especially these most common neurons, the pyramidal cells. And there's a property of neurons. Everyone knows, or most people know, that a neuron is a cell and it has this spike called an action potential and it sends information. But we now know that there's these spikes internal to the neuron. They're called dendritic spikes. They travel along the branches of the neuron and they don't leave the neuron. They're just internal only. They're far more dendruitic spikes than there are action potentials. Far more. They're happening all the time. And what we came to understand that those dendritic spikes, the ones that are occurring, are actually a form of prediction. They're telling the neurons.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“So I mentioned this earlier that prediction was our research agenda. We said, okay, how does the brain make a prediction? I'm about to grab this water bottle and my brain is predicting what I'm going to feel on all my parts of my fingers. If I felt something really odd on any part here, I'd notice it. So my brain is predicting what it's going to feel as I grab this thing. So, what is that? How does that manifest itself in neural tissue? Brain's made of neurons and there's chemicals and there's neurons and there's spikes and there's... And one argument could be that, well, when I'm predicting something, a neuron must be firing in advance. It's like, okay, this neuron represents what you're going to feel and it's firing. It's sending a spike. And certainly that happens to some extent. But our predictions are so ubiquitous.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Much as we can. I think our species is further along in that undeniably. Whether our theories are right or wrong, we can debate. But at least we have theories. We know that what the sun is and how fusion is and what black holes are. And we know general theory of relativity and no other animal has any of this knowledge. So in that sense, that we're special. Are we special in terms of the hierarchy of complexity in the universe? Probably not.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Some kind of significant place. I think there's one thing we could say that we are special, and again, only here on Earth. I'm not saying that, is that if we think about knowledge, What we know. We clearly human brains are the only brains that have a certain types of knowledge. We're the only brains on this earth to understand what the earth is, how old it is, the universe is a picture as a whole. The only organisms understand DNA and the origins of species. No other species on this planet has that knowledge. So if we think about I like to think about one of the endeavors of humanity is to understand the universe.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“You're bringing up the problems of complexity and complexity theory are a huge interesting problem in science. And I think we've made surprisingly little progress in understanding complex systems. In general. And so the Santa Fe Institute was founded to study this and even the scientist there will say it's really hard. We haven't really been able to figure out exactly that science isn't really congealed yet. We're still trying to figure out the basic elements of that science. Where does complexity come from and what is it and how you define it, whether it's DNA creating bodies or phenotypes or if it's individuals creating societies or ants and markets and so on? It's a very complex thing. I'm not a complexity theorist person, right? And it's interesting to ask, well, the brain itself is a complex system. So can we understand that? I think we've made a lot of progress understanding how the brain works. But I haven't brought it out to like, oh, well, where are we on the complexity spectrum? It's like, it's a great question.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Cortex, how we manifest as a human depends on the rest of our brain, what are our motivations? What are my desires? Am I a nice guy or not a nice guy? Am I a cheater or am I, you know, or not a cheater? How important different things are in my life? But the neocortex can be understood on its own. And I say that as a neuroscientist, I know there's all these interactions and I want to say I don't know them and we don't think about them. A layperson's point of view, you can say it's a modeling system. I don't generally think too much about the communal aspect of intelligence, which you've brought up a number of times already. So that's not really been my concern.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Music, we know that all high level planning and thinking occurs in the New York Cortex. If I were to say, you know, what part of your brain designed a computer and understands programming and creates music, it's all the neurocortex. So then that's an undeniable fact. But then there's other parts of our brain are important too, right? Our emotional states, our body regulating our body. So the way I like to look at it is can you understand the neocortex about the rest of the brain. And some people say you can't, and I think absolutely you can. It's not that they're not interacting, but you can understand. Can you understand the neurocortex without understanding the emotions of fear? Yes, you can. You can understand how this system works. It's just a modeling system. I make the analogy in the book that it's like a map of the world. And how that map is used depends on who's using it. So how our map of our world.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“I know, but it's nothing, it's not that We know that all high level vision, hearing, and touch happens in the neocortex. We know that all language occurs and is understood in the neocortex, whether that's spoken language, written language, sign language, whether language of mathematics, language of physics.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, obviously, again, I mentioned again in the beginning, it's about 70 to 75% of the volume of a human brain. So it dominates our brain in terms of size, not in terms of number of neurons, but in terms of size.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, our goal is to understand how the New York Cortex works. We can argue how essential that is to understand the human brain because it's not the entire human brain. You can argue how essential that is to understanding human intelligence. You can argue how essential it is to To sort of communal intelligence. Our goal was to understand the near quantity.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, there's no direction to it, but it just found out like, hey, if I took these elements and made more of them, what happens? And let's hook them up to the eyes and let's hook them up to the ears.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Is it the same mechanism? So we said it's much more likely the brain is using the same mechanism, which case, it would have these equivalent cell types. So it's basically the whole theory is built on the idea that these columns have reference frames and they're learning these models and these grid cells create these reference frames. So it's basically the major, in some sense, the major predictive part of this theory is that we will find these equivalent mechanisms in each column in the near cortex, which tells us that's what they're doing. They're learning these sensory motor models of the world. So just we're pretty confident that would happen, but now we're seeing the evidence.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Because it tells us, well, we're asking about the evolutionary origin of intelligence, right? So our theory is that these columns in the cortex are working on the same principles, their modeling systems. And it's hard to imagine how neurons do this. And so we said, hey, it's really hard to imagine how neurons could learn these models of things. I'm going to talk about the details of that if you want. But there's this other part of the brain. We know the learned models of environments. So could that mechanism that learn to model this room be used to learn a model, the water bottle?”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Come from something that wasn't universal, it came from something that was more specific. And so anyway, this led to our hypothesis that you would find grid cells and place cell equivalents in the neocortex. And when we first published our first papers on this theory, we didn't know of evidence for that. It turns out there was some, but we didn't know about it. And since then, so then we became aware of evidence for grid cells in certain parts of the neural cortex. And then now there's been new evidence coming out. There's some interesting papers that came out just January of this year. So one of our predictions was if this evolutionary hypothesis is correct, we would see grid cell place cell equivalents, cells that work like them to every column in the cortex. And that's starting to be seen.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Fundamentally distributed complete modeling systems. But that's our story we like to tell, I would guess it's likely largely right. But, you know, there's a lot of evidence supporting that story, this evolutionary story. The thing which brought me to this idea is that the human brain got big very quickly. So that led to the proposal a long time ago that, well, there's this common element just instead of creating new things, it just replicated something. We also are extremely flexible. We can learn things that we had no history about, right? And so that tells us that the learning algorithm is very generic. It's very kind of universal because it doesn't assume any prior knowledge about what it's learning. And so you combine those things together and you say, okay, well, how did that come about? Where did that universal algorithm come from?”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Keep learning the networks, they end up replicating an element, but you still need the entire network to do anything. Here, what's going on is each individual element is a complete learning system. This is why I can take a human brain, cut it in half, and it still works. It's pretty amazing.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“That mechanism we learned to map like a space was repackaged the same type of neurons was repackaged into a more compact form And that became the cortical column. And it was in some sense genericized, if that's a word. It was turned into a very specific thing about learning maps of environments to learning maps of anything, learning a model of anything, not just your space, but coffee cups and so on. And it got sort of repackaged into a more compact version, a more universal version, and then replicated So, the reason we're so flexible is we have a very generic version of this mapping algorithm, and we have 150,000 copies of it.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Mammals have this right, and almost any animal that knows where it is and get around must have some mapping system, must have some way of saying, I've learned a map of my environment. I have hummingbirds in my backyard. And they go to the same places all the time. They must know where they are. They just know where they are wonderfully. They're not just randomly flying around. They know particular flowers they come back to. So we all have this. And it turns out it's very tricky to get neurons to do this, to build a map of an environment. It's just, and so we now know there's these famous studies that still very active about place cells and grid cells and these other types of cells in the older parts of the brain and how they build these maps of the world. It's really clever. Obviously, be under a lot of evolutionary pressure over a long period of time to get good at this. So animals know where they are. What we think has happened, and there's a lot of evidence to suggest this, is that”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“We still have this neural mechanism in our brains. In the mammals, it's in the hippocampus and enterhinal cortex. These are older parts of the brain. And these are very well studied. We build a map of our environment. So these neurons in these parts of the brain know where I am in this room and where the door was and things like that.”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, we have a theory about it, and it's just that it's a theory. Theory goes as follows. As soon as living things started to move, they're not just floating in sea, they're not just a plant, you know, grounded someplace. As soon as they started the move, there was an advantage to moving intelligently, to moving in certain ways. And there's some very simple things you can do, bacteria or single-cell organisms can move towards a source of gradient of food or something like that. But an animal that might know where it is and know where it's been and how to get back to that place, or animal that might say, oh, there was a source of food someplace. How do I get to it? Or there was a danger. How do I get to it? Or there was a mate? How do I get to them? There was a big evolution advantage to that. So early on, there was a pressure to start understanding your environment, like where am I and where have I been and what happened in those different places?”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source
“So we started off with that observation. It's all this nonstop prediction. And I write about this in the book about, and then we ask, how do neurons actually make predictions physically like, what does the neuron do when it makes a prediction? Or the neural tissue does when it makes a prediction. And then we ask what are the mechanisms by how we build a model that allows you to make prediction. So we started with prediction as sort of the fundamental research agenda in some sense. And say, well, we understand how the brain makes predictions, we'll understand how it builds these models and how it learns, and that's a core of intelligence. So it was the key that got us in the door to say that is our research agenda. Understand predictions”
2021-08-08 · Lex Fridman Podcast · #208 – Jeff Hawkins: The Thousand Brains Theory of Intelligence · IDENTIFIED FROM THE TRANSCRIPT · source