Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Human brains can’t copy-paste knowledge, says Geoffrey Hinton. Learning has to happen the slow way: actions, trust, and rewiring connections over time. Even a full sentence only carries a tiny amount of information, so sharing knowledge is painfully low-bandwidth. That limitation is baked into being analog and having different brains.

Wes Roth

34,689 subscribers

26,663 views • 7 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Jason Candle says that when he's had free time as the Head Coach of #UConnFootball, he's been learning more about the history of the program, noting the great Coach Andy Baylock as a great resource: "This is a wealth of knowledge and a great human being who continues to give."

Jason Candle says that when he's had free time as the Head Coach of #UConnFootball, he's been learning more about the history of the program, noting the great Coach Andy Baylock as a great resource: "This is a wealth of knowledge and a great human being who continues to give."

Storrs Central

10,681 views • 1 month ago

Geoffrey Hinton says a big language model runs on about 1% of your brain's connections and still ends up knowing more than you: "So in your brain, you have a hundred trillion connections, roughly speaking. Okay. That's a lot. And you only live for about two billion seconds. That's not much." "If you compare how many seconds you live for, with how many connections you've got, you have a whole lot more connections than experiences." "Now with these neural nets, it's sort of the other way round. They only have of the order of a trillion connections. So like 1% of your connections, even in a big language model, many of them fewer, but they get thousands of times more experience than you." "So the big language models are solving the problem with not many connections, only a trillion. How do I make use of a huge amount of experience?" "And back propagation is really, really good at packing huge amounts of knowledge into not many connections." "But that's not the problem we're solving. We've got huge numbers of connections, not much experience. We need to sort of extract the most we can from each experience." Two to three billion seconds is the whole budget. Everything you know, you learned inside it. So evolution built you to squeeze a lot out of very little. Hinton's point is that a language model has the opposite problem and the opposite fix, and backprop turned out to be extremely good at that fix. Worth noticing what this predicts about failure. A system running on 1% of your wiring and thousands of times your experience is not going to fail the way you do. You fail from having seen too few examples. It fails from compressing too many into too little, and the compression is where the errors get made. That is a strange thing to be deploying into hospitals and courts with no way to inspect it. We test these systems by asking them questions, which tells you what came out. Nobody can yet look at a trillion connections and say what got packed in. - Geoffrey Hinton, Nobel laureate and Turing Award winner, on StarTalk (StarTalk) with Neil deGrasse Tyson.

Geoffrey Hinton says a big language model runs on about 1% of your brain's connections and still ends up knowing more than you: "So in your brain, you have a hundred trillion connections, roughly speaking. Okay. That's a lot. And you only live for about two billion seconds. That's not much." "If you compare how many seconds you live for, with how many connections you've got, you have a whole lot more connections than experiences." "Now with these neural nets, it's sort of the other way round. They only have of the order of a trillion connections. So like 1% of your connections, even in a big language model, many of them fewer, but they get thousands of times more experience than you." "So the big language models are solving the problem with not many connections, only a trillion. How do I make use of a huge amount of experience?" "And back propagation is really, really good at packing huge amounts of knowledge into not many connections." "But that's not the problem we're solving. We've got huge numbers of connections, not much experience. We need to sort of extract the most we can from each experience." Two to three billion seconds is the whole budget. Everything you know, you learned inside it. So evolution built you to squeeze a lot out of very little. Hinton's point is that a language model has the opposite problem and the opposite fix, and backprop turned out to be extremely good at that fix. Worth noticing what this predicts about failure. A system running on 1% of your wiring and thousands of times your experience is not going to fail the way you do. You fail from having seen too few examples. It fails from compressing too many into too little, and the compression is where the errors get made. That is a strange thing to be deploying into hospitals and courts with no way to inspect it. We test these systems by asking them questions, which tells you what came out. Nobody can yet look at a trillion connections and say what got packed in. - Geoffrey Hinton, Nobel laureate and Turing Award winner, on StarTalk (StarTalk) with Neil deGrasse Tyson.

Karl Mehta

659,516 views • 1 month ago

ELON: AI HAS DRAINED HUMAN KNOWLEDGE DRY - NOW DRINKING FROM ITS OWN WELL "You take the entire internet, all books ever written, all the interesting videos, and you distill that down into tokens, essentially bits of information. We've now exhausted all of that; the cumulative sum of human knowledge has been exhausted in AI training. That happened last year. So the only way to supplement that is with synthetic data, where the AI creates. It'll write an essay, or it'll come up with a thesis, and then it will grade itself. It'll go through this process of self-learning with synthetic data." Source: Elon Musk, Mark Penn, January 9th 2025

ELON: AI HAS DRAINED HUMAN KNOWLEDGE DRY - NOW DRINKING FROM ITS OWN WELL "You take the entire internet, all books ever written, all the interesting videos, and you distill that down into tokens, essentially bits of information. We've now exhausted all of that; the cumulative sum of human knowledge has been exhausted in AI training. That happened last year. So the only way to supplement that is with synthetic data, where the AI creates. It'll write an essay, or it'll come up with a thesis, and then it will grade itself. It'll go through this process of self-learning with synthetic data." Source: Elon Musk, Mark Penn, January 9th 2025

Mario Nawfal

1,938,848 views • 10 months ago

Scottish Labour has been pledging to cap bus fares since 2023. The owners of McGills buses donated £300,000 to Sarwar's Holyrood election campaign in full knowledge of this. So why is it only now that the policy is being tagged a gimmick and is apparently causing alarm?

Scottish Labour has been pledging to cap bus fares since 2023. The owners of McGills buses donated £300,000 to Sarwar's Holyrood election campaign in full knowledge of this. So why is it only now that the policy is being tagged a gimmick and is apparently causing alarm?

MSM Monitor

12,045 views • 3 months ago

Ilya Sutskever, co-founder and chief scientist of OpenAI: "Artificial intelligence is nothing but digital brains inside large computers." Sit with how flatly he says it. Not a metaphor, not marketing. The seat of intelligence in a human is a biological brain. The seat of intelligence in AI is an artificial one. Same thing, different substrate. Right now, he admits, it only "understands mostly, sort of." But that gap is temporary. In his words: "the day will come when the digital brains that live inside our computers will become as good and even better than our own biological brains. Computers will become smarter than us." He makes it concrete. Once an AI is built to be a doctor, with every medical paper and billions of hours of clinical experience, always on and almost free, "we will look back at today's health care similarly to how we look at 16th century dentistry." Hinton says it already understands. Ilya says the brain is just built differently. Either way, the argument was never whether it thinks. It was whether we were ready for the answer.

Ilya Sutskever, co-founder and chief scientist of OpenAI: "Artificial intelligence is nothing but digital brains inside large computers." Sit with how flatly he says it. Not a metaphor, not marketing. The seat of intelligence in a human is a biological brain. The seat of intelligence in AI is an artificial one. Same thing, different substrate. Right now, he admits, it only "understands mostly, sort of." But that gap is temporary. In his words: "the day will come when the digital brains that live inside our computers will become as good and even better than our own biological brains. Computers will become smarter than us." He makes it concrete. Once an AI is built to be a doctor, with every medical paper and billions of hours of clinical experience, always on and almost free, "we will look back at today's health care similarly to how we look at 16th century dentistry." Hinton says it already understands. Ilya says the brain is just built differently. Either way, the argument was never whether it thinks. It was whether we were ready for the answer.

Casper

69,481 views • 1 month ago

.Naval: You have a beautiful definition of knowledge, which most people don’t even try to tackle, about how knowledge perpetuates itself in the environment. You gave some really good examples. One was around genes. Successful, highly adapted genes contain a lot of knowledge and can cause themselves to be replicated because they’re survivors. In the same way, knowledge itself is a survivor, in that if you transmit to me the knowledge of how to build a computer, it’s an incredibly useful thing. I’m going to build more and more computers and that knowledge will be passed on. Your underlying point that you repeated here was if you want to understand the physical universe you have to understand knowledge, because it is the thing that over time takes over and changes more and more the universe—more than almost anything else. You have to understand all the explanations behind it. You can’t just say “particle collisions” because that explains everything, so it explains nothing. It’s not a useful level to operate at. Therefore, the things that create knowledge are uniquely influential in the universe. And as far as we know, there are only two systems that create knowledge. There’s evolution and there are humans. But is there a difference even between these two forms of knowledge creation, between evolution and between humans? David Deutsch: Yes. I have argued that the human way of creating knowledge is the ultimate one, that there aren’t any more powerful ones than that. This is the argument against the supernatural. Assuming that there is a form of knowledge creation that’s more powerful than ours is equivalent to invoking the supernatural, which is therefore a bad explanation—as invoking the supernatural always is. The difference between biological evolution and human creative thought is that biological evolution is inherently limited in its range. That’s because biological evolution has no foresight. It can’t see a problem and conjecture a solution. Whenever biological evolution produces a solution to something, it’s always before natural selection has even begun. This is Charles Darwin’s insight. This is the difference between Charles Darwin’s theory of evolution and the other theories of evolution that had been around for a century or more before that, including Charles Darwin’s grandfather and Lamarck. The thing they didn’t get is that the creation of knowledge in evolution begins before. That means that biological evolution can’t reach places that are not reachable by successive improvements, each of which allows a viable organism to exist. Creationists say that biological evolution has, in fact, reached things that are not reachable by incremental steps, each of which is a viable organism. They’re factually mistaken. The thing which they have in mind is the idea of a creator who can imagine things that don’t exist and who can create an idea that is not the culmination of a whole load of viable things. A thinking being can create something that’s a culmination of a whole load of non-viable things. Explanatory creativity makes humans unique Out of all the billions and billions of species that have ever existed, none of them has ever made a campfire, even though many of them would’ve been helped by having the genetic capacity to make campfires. The reason it didn’t happen in the biosphere is that there is no such thing as making a partially functional campfire; whereas there is, for example, with making hot water. The bombardier beetles squirt boiling water at their enemies. You can easily see that just squirting cold water at your enemies is not totally unhelpful. Then making it a bit hotter and a bit hotter. Squirting boiling water no doubt required many adaptations to make sure the beetle didn’t boil itself while it was making this boiling water. That happened because there was a sequence of steps in between, all of which were useful. But with campfires, it’s very hard to see how that could happen. Humans have explanatory creativity. Once you have that, you can get to the moon. You can cause asteroids which are heading towards the earth to turn around and go away. Perhaps no other planet in the universe has that power, and it has it only because of the presence of explanatory creativity on it.

.Naval: You have a beautiful definition of knowledge, which most people don’t even try to tackle, about how knowledge perpetuates itself in the environment. You gave some really good examples. One was around genes. Successful, highly adapted genes contain a lot of knowledge and can cause themselves to be replicated because they’re survivors. In the same way, knowledge itself is a survivor, in that if you transmit to me the knowledge of how to build a computer, it’s an incredibly useful thing. I’m going to build more and more computers and that knowledge will be passed on. Your underlying point that you repeated here was if you want to understand the physical universe you have to understand knowledge, because it is the thing that over time takes over and changes more and more the universe—more than almost anything else. You have to understand all the explanations behind it. You can’t just say “particle collisions” because that explains everything, so it explains nothing. It’s not a useful level to operate at. Therefore, the things that create knowledge are uniquely influential in the universe. And as far as we know, there are only two systems that create knowledge. There’s evolution and there are humans. But is there a difference even between these two forms of knowledge creation, between evolution and between humans? David Deutsch: Yes. I have argued that the human way of creating knowledge is the ultimate one, that there aren’t any more powerful ones than that. This is the argument against the supernatural. Assuming that there is a form of knowledge creation that’s more powerful than ours is equivalent to invoking the supernatural, which is therefore a bad explanation—as invoking the supernatural always is. The difference between biological evolution and human creative thought is that biological evolution is inherently limited in its range. That’s because biological evolution has no foresight. It can’t see a problem and conjecture a solution. Whenever biological evolution produces a solution to something, it’s always before natural selection has even begun. This is Charles Darwin’s insight. This is the difference between Charles Darwin’s theory of evolution and the other theories of evolution that had been around for a century or more before that, including Charles Darwin’s grandfather and Lamarck. The thing they didn’t get is that the creation of knowledge in evolution begins before. That means that biological evolution can’t reach places that are not reachable by successive improvements, each of which allows a viable organism to exist. Creationists say that biological evolution has, in fact, reached things that are not reachable by incremental steps, each of which is a viable organism. They’re factually mistaken. The thing which they have in mind is the idea of a creator who can imagine things that don’t exist and who can create an idea that is not the culmination of a whole load of viable things. A thinking being can create something that’s a culmination of a whole load of non-viable things. Explanatory creativity makes humans unique Out of all the billions and billions of species that have ever existed, none of them has ever made a campfire, even though many of them would’ve been helped by having the genetic capacity to make campfires. The reason it didn’t happen in the biosphere is that there is no such thing as making a partially functional campfire; whereas there is, for example, with making hot water. The bombardier beetles squirt boiling water at their enemies. You can easily see that just squirting cold water at your enemies is not totally unhelpful. Then making it a bit hotter and a bit hotter. Squirting boiling water no doubt required many adaptations to make sure the beetle didn’t boil itself while it was making this boiling water. That happened because there was a sequence of steps in between, all of which were useful. But with campfires, it’s very hard to see how that could happen. Humans have explanatory creativity. Once you have that, you can get to the moon. You can cause asteroids which are heading towards the earth to turn around and go away. Perhaps no other planet in the universe has that power, and it has it only because of the presence of explanatory creativity on it.

Deutsch Explains

186,329 views • 1 year ago

🔥Dan Bongino says “There is no way that Routh picked that spot without insider information” just like Butler he seemed to have knowledge and a known exploit would not even have the press/or a post standard there that day. Insider who has worked the course before knows the location well.

🔥Dan Bongino says “There is no way that Routh picked that spot without insider information” just like Butler he seemed to have knowledge and a known exploit would not even have the press/or a post standard there that day. Insider who has worked the course before knows the location well.

Johnny St.Pete

147,182 views • 1 year ago

Karl Popper on How We Gain Knowledge: ––Karl Popper: "People think, usually, that we acquire knowledge by opening our eyes and our ears and let the sensations stream into us, and they believe then that we record this like a camera. In my opinion, if we wish to get knowledge, we have to have a problem. It has to be knowledge of something. We have to find out something. We don't have to wait for information to stream into us, but we have to be inquisitive if we want to get knowledge. If we were passive, we would gain a confused mass of sensations or something like that, which we would hardly be able to understand and to convert into what one may call knowledge. Quite apart from that, perception is not really, in my opinion, the main source of our knowledge. The role of perception is to inform us about a momentary situation in our environment. But we couldn't really interpret our perceptions without knowing much more about our environment, namely, we know whether we are in a house or whether we are in a glacier. So we have two kinds of knowledge: this wider knowledge of a frame in which we orientate ourselves, and the momentary perception which gives us information about the situation at that particular moment. And it is only this situation in which we can use our perception. So we have theoretical knowledge and, if you like, the momentary practical challenge to our theoretical knowledge. And here comes perception in."

Karl Popper on How We Gain Knowledge: ––Karl Popper: "People think, usually, that we acquire knowledge by opening our eyes and our ears and let the sensations stream into us, and they believe then that we record this like a camera. In my opinion, if we wish to get knowledge, we have to have a problem. It has to be knowledge of something. We have to find out something. We don't have to wait for information to stream into us, but we have to be inquisitive if we want to get knowledge. If we were passive, we would gain a confused mass of sensations or something like that, which we would hardly be able to understand and to convert into what one may call knowledge. Quite apart from that, perception is not really, in my opinion, the main source of our knowledge. The role of perception is to inform us about a momentary situation in our environment. But we couldn't really interpret our perceptions without knowing much more about our environment, namely, we know whether we are in a house or whether we are in a glacier. So we have two kinds of knowledge: this wider knowledge of a frame in which we orientate ourselves, and the momentary perception which gives us information about the situation at that particular moment. And it is only this situation in which we can use our perception. So we have theoretical knowledge and, if you like, the momentary practical challenge to our theoretical knowledge. And here comes perception in."

Karl Popper Quotes

115,237 views • 4 months ago

Galen Druke (Galen Druke) interviewed me about common knowledge, the topic of my new book (link in thread): Me: What common knowledge does in informal interactions is it ratifies social relationships. So if two people are friends, if they’re lovers, if one of them is dominant and the other is subordinate—that is, one always gets it this way—these exist because each party knows the other one knows they exist. And they survive by being common knowledge. Sometimes we don’t want to destroy a relationship, and so we keep things out of common knowledge by using euphemism or innuendo or genteel hypocrisy. Druke: What’s an example of this? Me: At the end of a date, you’ve got a couple of friends and one says, “Hey, do you want to kind of come up for coffee—or Netflix and chill?” That’s very different from, “Do you want to have sex?” even though if they’re both grownups, they both know that it’s having sex. So there’s a denial of common knowledge, which would allow them—if the overture is not reciprocated—to go back to being platonic friends or workplace colleagues.

Galen Druke (Galen Druke) interviewed me about common knowledge, the topic of my new book (link in thread): Me: What common knowledge does in informal interactions is it ratifies social relationships. So if two people are friends, if they’re lovers, if one of them is dominant and the other is subordinate—that is, one always gets it this way—these exist because each party knows the other one knows they exist. And they survive by being common knowledge. Sometimes we don’t want to destroy a relationship, and so we keep things out of common knowledge by using euphemism or innuendo or genteel hypocrisy. Druke: What’s an example of this? Me: At the end of a date, you’ve got a couple of friends and one says, “Hey, do you want to kind of come up for coffee—or Netflix and chill?” That’s very different from, “Do you want to have sex?” even though if they’re both grownups, they both know that it’s having sex. So there’s a denial of common knowledge, which would allow them—if the overture is not reciprocated—to go back to being platonic friends or workplace colleagues.

Steven Pinker

22,350 views • 10 months ago

"This internship experience has been truly unique, allowing me to gain direct insight into the professional environment of the United Nations and to apply my academic knowledge in a meaningful way." Aicha is an intern at UN Human Rights and this is her #InternTestimonial.

"This internship experience has been truly unique, allowing me to gain direct insight into the professional environment of the United Nations and to apply my academic knowledge in a meaningful way." Aicha is an intern at UN Human Rights and this is her #InternTestimonial.

United Nations Geneva

33,157 views • 26 days ago

I am a physicist and I'm profoundly opposed to any idea of non-physical explanations that contradict physics. So that's a no-no and really doesn't make sense. However, there are ways in which both emergent properties such as minds and life and so on have an effect. And as you said, also abstractions. Now the fact that the theory of good explanations led to the idea that abstractions are real things was slightly surprising to me. I wasn't expecting the link, at least wasn't expecting it to be so strong as it is. But the thing is, if you think about how to explain events, physical events like a footprint on the moon, how do you explain how that happened? Well, it happened because of human ideas, of science. And human ideas, you could say in this reductionist sense that as you rightly say is the prevailing mode of explanation and the prevailing idea is to look down on other modes of explanation, that those ideas are nothing more than configurations of atoms. So some physicists, some rocket scientists put their brain into certain configurations of atoms and those atoms then acted on other atoms which then ended up making a footprint on the moon. Now what that misses is the explanation of why certain configurations of atoms put footprints on the moon while others, the overwhelming majority of configurations that human brains, even human brains have been put into in history, do not have that effect. And it's because there's a certain type of information. And this information can't in my view be reduced to statements about atoms because if you think about what that information does, it is in brains but the same information then gets transferred into, let's say, sound waves in air and then it gets transferred into ink on paper and then it gets transferred into magnetic domains inside a computer which then control a machine that instantiates those ideas in bits of steel and silicon and so on and so on. There's an immense chain of instantiations of the same information. And it's only special kinds of information that have this property that they are preserved and instantiated in successive physical modes. So what is being transmitted, what is having the causal effect is not the atoms but the fact that the atoms instantiate certain kinds of information and not other kinds. So therefore it is the information that is having the causal effect. If a particular instantiation of that information were damaged, then processes would come along to fix it, whether or not they could fix the physical instantiation. For example, if the computer goes wrong, then we don't use the corrupted information. We go back and rescue the information from a different computer and we throw away the atoms that at one point instantiated it. So the information causes itself to remain in existence. Now I think there's no way out of that mode of explanation. And if explanation is going to be the fundamental thing about our criterion, for example, about what is or isn't real, then we have to say that information and this particular kind which we call knowledge is real and really does cause things. David Deutsch

I am a physicist and I'm profoundly opposed to any idea of non-physical explanations that contradict physics. So that's a no-no and really doesn't make sense. However, there are ways in which both emergent properties such as minds and life and so on have an effect. And as you said, also abstractions. Now the fact that the theory of good explanations led to the idea that abstractions are real things was slightly surprising to me. I wasn't expecting the link, at least wasn't expecting it to be so strong as it is. But the thing is, if you think about how to explain events, physical events like a footprint on the moon, how do you explain how that happened? Well, it happened because of human ideas, of science. And human ideas, you could say in this reductionist sense that as you rightly say is the prevailing mode of explanation and the prevailing idea is to look down on other modes of explanation, that those ideas are nothing more than configurations of atoms. So some physicists, some rocket scientists put their brain into certain configurations of atoms and those atoms then acted on other atoms which then ended up making a footprint on the moon. Now what that misses is the explanation of why certain configurations of atoms put footprints on the moon while others, the overwhelming majority of configurations that human brains, even human brains have been put into in history, do not have that effect. And it's because there's a certain type of information. And this information can't in my view be reduced to statements about atoms because if you think about what that information does, it is in brains but the same information then gets transferred into, let's say, sound waves in air and then it gets transferred into ink on paper and then it gets transferred into magnetic domains inside a computer which then control a machine that instantiates those ideas in bits of steel and silicon and so on and so on. There's an immense chain of instantiations of the same information. And it's only special kinds of information that have this property that they are preserved and instantiated in successive physical modes. So what is being transmitted, what is having the causal effect is not the atoms but the fact that the atoms instantiate certain kinds of information and not other kinds. So therefore it is the information that is having the causal effect. If a particular instantiation of that information were damaged, then processes would come along to fix it, whether or not they could fix the physical instantiation. For example, if the computer goes wrong, then we don't use the corrupted information. We go back and rescue the information from a different computer and we throw away the atoms that at one point instantiated it. So the information causes itself to remain in existence. Now I think there's no way out of that mode of explanation. And if explanation is going to be the fundamental thing about our criterion, for example, about what is or isn't real, then we have to say that information and this particular kind which we call knowledge is real and really does cause things. David Deutsch

Deutsch Explains

45,735 views • 2 years ago

“The thing that happened with AGI and pretraining is that in some sense they overshot the target. You will realize that a human being is not an AGI. Because a human being lacks a huge amount of knowledge. Instead, we rely on continual learning. If I produce a super intelligent 15 -year -old, they don't know very much at all. A great student, very eager. [You can say,] ‘You go and be a programmer. You go and be a doctor. Go and learn.’ So you could imagine that the deployment itself will involve some kind of a learning trial and error period. It's a process as opposed to, you drop the finished thing.” Ilya Sutskever

“The thing that happened with AGI and pretraining is that in some sense they overshot the target. You will realize that a human being is not an AGI. Because a human being lacks a huge amount of knowledge. Instead, we rely on continual learning. If I produce a super intelligent 15 -year -old, they don't know very much at all. A great student, very eager. [You can say,] ‘You go and be a programmer. You go and be a doctor. Go and learn.’ So you could imagine that the deployment itself will involve some kind of a learning trial and error period. It's a process as opposed to, you drop the finished thing.” Ilya Sutskever

Dwarkesh Patel

661,619 views • 9 months ago

Your attention please: Is there a mother on the plane? ✈️ 😂 I often write about the brain development of young children. But did you know that babies’ brains aren’t the only ones growing and changing after their arrival? It’s time we talked about “Parent Brain.” A growing body of evidence suggests that the brains of primary caregivers (mothers, fathers and even non-biological parents) undergo change during the transition to parenthood. Just as infancy is a critical developmental window for children, parents’ brains adapt as a result of hormonal activations designed to stimulate caregiving instincts. Did you know, for example, that the sound of a crying baby stimulates activity in the brains of parents in ways that are not experienced by non-parents? Just as babies’ reflexes are designed to optimize their chances at thriving and surviving, so too does biology work to ensure their wellbeing in the brains of their parents. Accompanying these changes is a specialized set of parental knowledge - like how to collapse a double stroller. 😀 Witness as a group of (presumptive) non-parents have a go at folding one up on an airport tarmac. Their lesson of the day: Being a parent is not as easy as it looks. 🎥 lateplaneguy TT

Your attention please: Is there a mother on the plane? ✈️ 😂 I often write about the brain development of young children. But did you know that babies’ brains aren’t the only ones growing and changing after their arrival? It’s time we talked about “Parent Brain.” A growing body of evidence suggests that the brains of primary caregivers (mothers, fathers and even non-biological parents) undergo change during the transition to parenthood. Just as infancy is a critical developmental window for children, parents’ brains adapt as a result of hormonal activations designed to stimulate caregiving instincts. Did you know, for example, that the sound of a crying baby stimulates activity in the brains of parents in ways that are not experienced by non-parents? Just as babies’ reflexes are designed to optimize their chances at thriving and surviving, so too does biology work to ensure their wellbeing in the brains of their parents. Accompanying these changes is a specialized set of parental knowledge - like how to collapse a double stroller. 😀 Witness as a group of (presumptive) non-parents have a go at folding one up on an airport tarmac. Their lesson of the day: Being a parent is not as easy as it looks. 🎥 lateplaneguy TT

Dan Wuori

242,294 views • 3 years ago

At HKUST(GZ)'s Global Leaders Forum, Professor Ye QI, Dean of HKUST(GZ)'s Society Hub, posed a thought-provoking question as the forum moderator: When it's so easy to get new knowledge, what can we teach our next generation? Professor Dawn FRESHWATER, Vice-Chancellor of the University of Auckland and member of HKUST(GZ)'s Global Strategic Advisory Board, offered her inspiring perspective: It's easy to access existing knowledge, but new knowledge is different. It comes from being human and being engaged in the world in a meaningful way. So challenge yourself to step out, and live an unfiltered life. Watch the video for the full dialogue.

At HKUST(GZ)'s Global Leaders Forum, Professor Ye QI, Dean of HKUST(GZ)'s Society Hub, posed a thought-provoking question as the forum moderator: When it's so easy to get new knowledge, what can we teach our next generation? Professor Dawn FRESHWATER, Vice-Chancellor of the University of Auckland and member of HKUST(GZ)'s Global Strategic Advisory Board, offered her inspiring perspective: It's easy to access existing knowledge, but new knowledge is different. It comes from being human and being engaged in the world in a meaningful way. So challenge yourself to step out, and live an unfiltered life. Watch the video for the full dialogue.

HKUST Guangzhou

90,219 views • 5 months ago

ELON MUSK: We are already a *Cyborg*.....people don't realize we are already a cyborg because we are so well integrated with our phones and our computers The phone is almost like an extension of yourself. If you forget your phone, it's like a missing limb But the bandwidth the communication bandwidth to the phone is very low, especially input. In fact, input bandwidth to computers has actually gone down because of typing with two thumbs as opposed to ten fingers That is a big reduction in bandwidth. Input bandwidth has gone up because of video and imagery, so input bandwidth is many orders of magnitude greater than output bandwidth But at a certain point, assuming a benign scenario with AI, we will just be too slow. Let’s say a computer that has an exaflop, or many exaflops, of compute capability a millisecond is an eternity, and to us, it's nothing Human speech to a computer will sound like very slow tonal wheezing, kind of like whale sounds" - ELON MUSK

ELON MUSK: We are already a Cyborg.....people don't realize we are already a cyborg because we are so well integrated with our phones and our computers The phone is almost like an extension of yourself. If you forget your phone, it's like a missing limb But the bandwidth the communication bandwidth to the phone is very low, especially input. In fact, input bandwidth to computers has actually gone down because of typing with two thumbs as opposed to ten fingers That is a big reduction in bandwidth. Input bandwidth has gone up because of video and imagery, so input bandwidth is many orders of magnitude greater than output bandwidth But at a certain point, assuming a benign scenario with AI, we will just be too slow. Let’s say a computer that has an exaflop, or many exaflops, of compute capability a millisecond is an eternity, and to us, it's nothing Human speech to a computer will sound like very slow tonal wheezing, kind of like whale sounds" - ELON MUSK

X Freeze

27,930 views • 7 months ago

this was the most important bit of the ilya interview imo. humans are not AGI, and LLMs won’t become like humans with more scaling. humans lack a huge amount of knowledge and have insanely good “continual learning” powered by extremely good reward functions (except for addiction) that guide them. and so it’s more about the learning rather than knowledge. the term AGI was coined as a response to the narrow AI which was only capable of intelligence in a specific domain (chess, game, code, etc) but General intelligence is able to learn different topics because that’s what “learning” is about. pre-training was thought to be the solution to reaching AGI because you train AI on so many different topics. but they have “overshot” that target. amazing perspective.

this was the most important bit of the ilya interview imo. humans are not AGI, and LLMs won’t become like humans with more scaling. humans lack a huge amount of knowledge and have insanely good “continual learning” powered by extremely good reward functions (except for addiction) that guide them. and so it’s more about the learning rather than knowledge. the term AGI was coined as a response to the narrow AI which was only capable of intelligence in a specific domain (chess, game, code, etc) but General intelligence is able to learn different topics because that’s what “learning” is about. pre-training was thought to be the solution to reaching AGI because you train AI on so many different topics. but they have “overshot” that target. amazing perspective.

ℏεsam

53,444 views • 9 months ago

In Ag…… let’s be honest we know so very little, we just hope to capture a bit of knowledge each opportunity we get. We should learn from one another not cry about someone’s ideas because they are different then what you learned or were taught. History teaches us a lot, but it doesn’t mean you can’t move forward, it’s a constant cycle of learning. And no one learns without others! It’s a team game that we are all in together. The guy that says I can’t trust that guy as he sells that seed or that fertilizer or that foliar is going to see rough times. As learning is opening your eyes and ears to ideas, and adding them to your library full of knowledge from your own experiences. That’s how something improves. It’s not the same thing every year and it’s not changing everything all at once. It’s bringing ideas and practices together to make it all work and bridge the gap.

In Ag…… let’s be honest we know so very little, we just hope to capture a bit of knowledge each opportunity we get. We should learn from one another not cry about someone’s ideas because they are different then what you learned or were taught. History teaches us a lot, but it doesn’t mean you can’t move forward, it’s a constant cycle of learning. And no one learns without others! It’s a team game that we are all in together. The guy that says I can’t trust that guy as he sells that seed or that fertilizer or that foliar is going to see rough times. As learning is opening your eyes and ears to ideas, and adding them to your library full of knowledge from your own experiences. That’s how something improves. It’s not the same thing every year and it’s not changing everything all at once. It’s bringing ideas and practices together to make it all work and bridge the gap.

Jason Schley

13,586 views • 10 months ago