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David Deutsch says all computation from humans to LLMs shares the same fundamental power: the universal Turing machine The difference is only in programs and outputs. But AGI is different; we don't even understand it in principle. "so the true sign would be a theory, not a machine"

Haider.

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11,720 просмотров • 11 месяцев назад •via X (Twitter)

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Sam Altman talks about GPT-8 with David Deutsch, one of the world's most brilliant physicists Sam asks him if GPT8 solved quantum gravity, would that convince him that AGI is achieved. David Deutsch argues the Turing Test is no real measure, LLMs, even "GPT-8" lack true creative inspiration, and AGI won’t fit into fixed-test evaluations. But if GPT8 can solve quantum gravity that would be AGI for him. --- From 'Deutsch Explains' YT Channel

Sam Altman talks about GPT-8 with David Deutsch, one of the world's most brilliant physicists Sam asks him if GPT8 solved quantum gravity, would that convince him that AGI is achieved. David Deutsch argues the Turing Test is no real measure, LLMs, even "GPT-8" lack true creative inspiration, and AGI won’t fit into fixed-test evaluations. But if GPT8 can solve quantum gravity that would be AGI for him. --- From 'Deutsch Explains' YT Channel

Rohan Paul

319,846 просмотров • 10 месяцев назад

David Chalmers says it is possible for an AI system to be conscious because the brain itself is a machine that produces consciousness, so we know this is possible in principle

David Chalmers says it is possible for an AI system to be conscious because the brain itself is a machine that produces consciousness, so we know this is possible in principle

Tsarathustra

526,587 просмотров • 2 лет назад

.David Deutsch: The equivalent of consilience, that is, the unified meta-theory, as you put it, for all sciences, and I think actually more than a meta-theory, because I think more links them than just the structure and methodology and so on, was discovered by Popper. Again, I don't know whether this is historically the order in which things happen, but he is famous for his political philosophy and for his philosophy of science, and he found at one point that they are the same, that they both are about problems and about the fact that there is no such instruction from without, there is only conjecture from within. So that's why Lamarckism is false and Darwinism is true, and that's why group selection is false and individual selection is true, and so on. So I think it's already there in Popper. I think there's a lot more to it, and I tried to add another couple of things to it, so quantum theory and computation, but there's a lot that isn't in it, like consciousness and creativity and so on, that we have no idea of how those work and how they fit in with those other things. Gad Saad: Forgive me for interrupting you, David, I'm sorry. There is a book by Dean Simington, who's a psychologist out of, I think, UC Davis, that actually offers a Darwinian account for creativity. It's actually quite mind-blowing. So keep that in mind. I can give you the reference later, but go ahead. David Deutsch: I don't read such things unless they've already made an AGI. Gad Saad: I see. Okay, fair enough. David Deutsch: If they can't make an AGI, then they haven't got the full theory. They might have an idea for a theory, but then Popper has an idea for a theory, but he couldn't make one either. And Turing thought that there'd be an AGI by the year 2000, and that it would require two megabytes of memory. Now, he's obviously wrong about the year 2000, but two megabytes of memory, I reckon that's what it'll be. In other words, these large language models and all this massive computer power is going in entirely the wrong direction. The answer will be a philosophical breakthrough, which will allow, once we understand what we're trying to make, it will be relatively easy to make it with relatively few computational resources.

.David Deutsch: The equivalent of consilience, that is, the unified meta-theory, as you put it, for all sciences, and I think actually more than a meta-theory, because I think more links them than just the structure and methodology and so on, was discovered by Popper. Again, I don't know whether this is historically the order in which things happen, but he is famous for his political philosophy and for his philosophy of science, and he found at one point that they are the same, that they both are about problems and about the fact that there is no such instruction from without, there is only conjecture from within. So that's why Lamarckism is false and Darwinism is true, and that's why group selection is false and individual selection is true, and so on. So I think it's already there in Popper. I think there's a lot more to it, and I tried to add another couple of things to it, so quantum theory and computation, but there's a lot that isn't in it, like consciousness and creativity and so on, that we have no idea of how those work and how they fit in with those other things. Gad Saad: Forgive me for interrupting you, David, I'm sorry. There is a book by Dean Simington, who's a psychologist out of, I think, UC Davis, that actually offers a Darwinian account for creativity. It's actually quite mind-blowing. So keep that in mind. I can give you the reference later, but go ahead. David Deutsch: I don't read such things unless they've already made an AGI. Gad Saad: I see. Okay, fair enough. David Deutsch: If they can't make an AGI, then they haven't got the full theory. They might have an idea for a theory, but then Popper has an idea for a theory, but he couldn't make one either. And Turing thought that there'd be an AGI by the year 2000, and that it would require two megabytes of memory. Now, he's obviously wrong about the year 2000, but two megabytes of memory, I reckon that's what it'll be. In other words, these large language models and all this massive computer power is going in entirely the wrong direction. The answer will be a philosophical breakthrough, which will allow, once we understand what we're trying to make, it will be relatively easy to make it with relatively few computational resources.

Deutsch Explains

33,398 просмотров • 1 год назад

KL divergence is a fundamental concept used in machine learning, from optimization a neural net to RL training of LLMs. but here is what it actually means:

KL divergence is a fundamental concept used in machine learning, from optimization a neural net to RL training of LLMs. but here is what it actually means:

ℏεsam

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Francois Chollet says LLMs aren't enough for human-like continual learning They store skills as vector programs learned via gradient descent — not efficient, not adaptive True AGI needs to learn from experience and generalize fast "LLMs can be part of AGI, but not the solution"

Francois Chollet says LLMs aren't enough for human-like continual learning They store skills as vector programs learned via gradient descent — not efficient, not adaptive True AGI needs to learn from experience and generalize fast "LLMs can be part of AGI, but not the solution"

Haider.

50,251 просмотров • 9 месяцев назад

Demis Hassabis ans the question "Why not make an alternate AI that works in synchrony with humans instead of trying to replace human intelligence?" He says AGI isn’t about replacing humans project—it’s a science question about what counts as truly general computation, plus an economics reality. The brain is our only known roughly Turing-like machine, so “general intelligence” means that level of flexibility. Companies chase it because general tools cheaply transfer everywhere, "generality" wins because it scales better --- From 'Varun Mayya' YT channel (link in comment)

Demis Hassabis ans the question "Why not make an alternate AI that works in synchrony with humans instead of trying to replace human intelligence?" He says AGI isn’t about replacing humans project—it’s a science question about what counts as truly general computation, plus an economics reality. The brain is our only known roughly Turing-like machine, so “general intelligence” means that level of flexibility. Companies chase it because general tools cheaply transfer everywhere, "generality" wins because it scales better --- From 'Varun Mayya' YT channel (link in comment)

Rohan Paul

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Peter Thiel: I didn't want to believe Elon but then it was the sense in which I felt he was correct: if Trump could not win in 2024 against The Machine, The Machine would always win — And if The Machine always wins, you no longer have a democracy. If The Machine could defeat Trump, I thought it was reasonable that it would gain even more power and somehow be unbeatable and the country would become a one party state.

Peter Thiel: I didn't want to believe Elon but then it was the sense in which I felt he was correct: if Trump could not win in 2024 against The Machine, The Machine would always win — And if The Machine always wins, you no longer have a democracy. If The Machine could defeat Trump, I thought it was reasonable that it would gain even more power and somehow be unbeatable and the country would become a one party state.

ALEX

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.Naval: Every human is a lottery ticket bet on the future of the species. One of the things that you really learn when you read David Deutsch’s theories and you authenticate them for yourself is you realize humans are universal explainers. That means everything that we know in the universe follows the laws of physics, and there’s no reason to believe otherwise. If you think otherwise, then please present your better theory that explains the world. If you can’t do that, then you have to go with the laws of physics. Well, the laws of physics are completely computable. They can fit inside a Turing machine or computer, and a computer can simulate the laws of physics with arbitrary accuracy, limited only by the specific power of that computer. If you increase the power of that computer, you can simulate them more accurately. So humans already simulate—in our minds we simulate—and through our computers we simulate the weather, we simulate quasars, we even simulate human systems. We simulate the economy. We simulate all kinds of things. So anything that can be understood, we can understand in our minds. This is something the AGI people get wrong when they talk about superintelligence. There is nothing out there that can understand something fundamentally that we can’t understand. It might be faster at it, it might have more compute, it might have more memory, but there’s no concept that it can understand that we can’t ourselves understand. So we are maximal universal explainers. That means every human is capable of unbounded creativity. Anyone could be the next Einstein or Fermi or Elon Musk or Jeff Bezos or Jonas Salk or whatever. So we can create anything. And if we can create anything, every human is a lottery ticket bet on the future of the species.

.Naval: Every human is a lottery ticket bet on the future of the species. One of the things that you really learn when you read David Deutsch’s theories and you authenticate them for yourself is you realize humans are universal explainers. That means everything that we know in the universe follows the laws of physics, and there’s no reason to believe otherwise. If you think otherwise, then please present your better theory that explains the world. If you can’t do that, then you have to go with the laws of physics. Well, the laws of physics are completely computable. They can fit inside a Turing machine or computer, and a computer can simulate the laws of physics with arbitrary accuracy, limited only by the specific power of that computer. If you increase the power of that computer, you can simulate them more accurately. So humans already simulate—in our minds we simulate—and through our computers we simulate the weather, we simulate quasars, we even simulate human systems. We simulate the economy. We simulate all kinds of things. So anything that can be understood, we can understand in our minds. This is something the AGI people get wrong when they talk about superintelligence. There is nothing out there that can understand something fundamentally that we can’t understand. It might be faster at it, it might have more compute, it might have more memory, but there’s no concept that it can understand that we can’t ourselves understand. So we are maximal universal explainers. That means every human is capable of unbounded creativity. Anyone could be the next Einstein or Fermi or Elon Musk or Jeff Bezos or Jonas Salk or whatever. So we can create anything. And if we can create anything, every human is a lottery ticket bet on the future of the species.

Arjun Khemani

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#WATCH | Delhi: Chief Election Commissioner Gyanesh Kumar says, "The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019." "We have to understand the difference between a machine-readable voter list and a searchable voter list. You can search the voter list available on the Election Commission website by entering the EPIC number. You can also download it. This is not called machine-readable. Regarding machine-readable, in 2019, the Supreme Court also studied this subject in depth and found that giving a machine-readable electoral roll can violate the privacy of the voter... The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019..."

#WATCH | Delhi: Chief Election Commissioner Gyanesh Kumar says, "The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019." "We have to understand the difference between a machine-readable voter list and a searchable voter list. You can search the voter list available on the Election Commission website by entering the EPIC number. You can also download it. This is not called machine-readable. Regarding machine-readable, in 2019, the Supreme Court also studied this subject in depth and found that giving a machine-readable electoral roll can violate the privacy of the voter... The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019..."

ANI

281,884 просмотров • 1 год назад

.David Deutsch: "What's currently called AI and AGI are not only different from each other, they are very close to being the exact opposites of each other. The reason is that an AI, current AI is like an AI that diagnoses diseases or an AI that plays chess or an AI that controls a huge factory. Those things have objective functions, that is they have a function that they are designed to maximize and that is why they are used in those particular applications. Or in military terms, you could say the objective is to hit the target. You might say the objective is to hit the target unless some thing specified, but it's a specified thing comes up in which case don't hit the target and so on. This is, as I said, almost the opposite of what humans do when humans think. For a start, the AI has to be obedient, that is it has to actually do the things it is programmed to do, whereas a human is fundamentally disobedient, especially when being creative. When a human plays chess, they are performing a completely different kind of computation. They don't do the same things, they don't investigate the same possibilities that the artificial chess playing machine does, because the artificial one is capable of looking at billions and billions of possibilities, whereas the human can only look at hundreds or something. They are doing something completely different. Another difference is that the human can explain, can write a book later, having become world champion, can write a book saying how I did it, as the computer program that beats the world champion can write no such book, because it has no idea how it did it. It was just following a program. I was doing this and that and that and none of that is illuminating. Also, third thing, the chess player can decide I don't want to play chess anymore, from now on I will play Go or from now on I will play tennis. If commanded to play chess, the functionality will deteriorate completely. Those things are different. What we want in an AGI is that it behaves in a way that cannot be specified in advance, because if you specified it, you would already have the answer. The AGI program has to give unexpected answers, answers to questions we didn't even know how to ask."

.David Deutsch: "What's currently called AI and AGI are not only different from each other, they are very close to being the exact opposites of each other. The reason is that an AI, current AI is like an AI that diagnoses diseases or an AI that plays chess or an AI that controls a huge factory. Those things have objective functions, that is they have a function that they are designed to maximize and that is why they are used in those particular applications. Or in military terms, you could say the objective is to hit the target. You might say the objective is to hit the target unless some thing specified, but it's a specified thing comes up in which case don't hit the target and so on. This is, as I said, almost the opposite of what humans do when humans think. For a start, the AI has to be obedient, that is it has to actually do the things it is programmed to do, whereas a human is fundamentally disobedient, especially when being creative. When a human plays chess, they are performing a completely different kind of computation. They don't do the same things, they don't investigate the same possibilities that the artificial chess playing machine does, because the artificial one is capable of looking at billions and billions of possibilities, whereas the human can only look at hundreds or something. They are doing something completely different. Another difference is that the human can explain, can write a book later, having become world champion, can write a book saying how I did it, as the computer program that beats the world champion can write no such book, because it has no idea how it did it. It was just following a program. I was doing this and that and that and none of that is illuminating. Also, third thing, the chess player can decide I don't want to play chess anymore, from now on I will play Go or from now on I will play tennis. If commanded to play chess, the functionality will deteriorate completely. Those things are different. What we want in an AGI is that it behaves in a way that cannot be specified in advance, because if you specified it, you would already have the answer. The AGI program has to give unexpected answers, answers to questions we didn't even know how to ask."

Deutsch Explains

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This would be funny if it weren’t so true. We keep paying taxes to the machine and everybody claps like lobotomized seals like nothing is wrong. It’s time to break the machine.

This would be funny if it weren’t so true. We keep paying taxes to the machine and everybody claps like lobotomized seals like nothing is wrong. It’s time to break the machine.

AmericanPapaBear™

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Just designed a new machine. It’s called a wire de-coiler. As the name suggests, it de-coils the wire to be fed into the machine. It works in tandem with our CNC machines. This is a bought out machine till now but we did the math and we can actually make it for roughly the price. Another machine to be made in-house soon!

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Richard Sutton says that the current dominance of LLMs is a "momentary fixation" the real breakthroughs will come from scaling computation, not building AI systems based on how humans think they work. LLMs will not be the leading edge of AI for more than another decade, perhaps even half a decade.

Richard Sutton says that the current dominance of LLMs is a "momentary fixation" the real breakthroughs will come from scaling computation, not building AI systems based on how humans think they work. LLMs will not be the leading edge of AI for more than another decade, perhaps even half a decade.

Haider.

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.David Deutsch: "I've come to think of free will in terms of creating knowledge. So we have free will if we can bring something objectively new into the universe. Prof. Brian Keating: Will computers have free will? David Deutsch: It's not computers, it's computer programs. Computer programs will have free will when the problem of AGI is solved. Of course, if we destroy ourselves before we solve that, then they won't. But I expect that we won't destroy ourselves, and I expect that the problem of AGI will be solved, and the resulting programs will have free will."

.David Deutsch: "I've come to think of free will in terms of creating knowledge. So we have free will if we can bring something objectively new into the universe. Prof. Brian Keating: Will computers have free will? David Deutsch: It's not computers, it's computer programs. Computer programs will have free will when the problem of AGI is solved. Of course, if we destroy ourselves before we solve that, then they won't. But I expect that we won't destroy ourselves, and I expect that the problem of AGI will be solved, and the resulting programs will have free will."

Deutsch Explains

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Iranian people with a big sign in a rally against the Islamic regime of Iran that says; “We not only sh** to your Islam but also we Sh** to the other Islam that you say it is the true one and it is not like this one”

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Physicist Brian Cox says consciousness is the most complex emergent phenomenon we know, but it still comes from underlying laws In principle, a powerful enough computer could model the brain AI and AGI raise this question: "we still don't know how consciousness emerges from the brain"

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Haider.

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David Deutsch calls it the Principle of Optimism. The principle of optimism says that anything not forbidden by the laws of physics is possible with enough knowledge, which can be acquired through trial and error.

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