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A NOBEL WINNING PHYSICIST ARGUED THAT NO AI, NO MATTER HOW POWERFUL, WILL EVER TRULY UNDERSTAND A SINGLE THING IT SAYS. HIS REASON IS NOT COMPUTE OR DATA -- IT IS A MATH THEOREM FROM THE 1930s THAT SAYS SOME TRUTHS CAN BE SEEN BUT NEVER COMPUTED 81 minutes...

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276,520 просмотров • 1 месяц назад •via X (Twitter)

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Adding more GPUs will never make a machine conscious. Nobel Prize-winning physicist Roger Penrose just dismantled the entire AI race’s core assumption. Right now, the industry operates on one belief. Build massive data centers. Scale the models. AGI will just “wake up.” Penrose destroys this completely. Penrose: “There is this sort of view that once you make a computer complicated enough or something, it suddenly becomes aware. I just don’t believe that. There’s no reason to believe that.” A machine can compute better than any human alive. But computation is not awareness. Penrose: “There is something quite different involved in understanding things, in being aware of things, of feeling things, which is not part of computations.” We’re confusing rule-following with actual intelligence. Penrose: “The keyword is the word ‘understanding.’ You can follow rules alright, but we don’t understand what we’re doing. The understanding is the key point.” Models today are exceptional at processing data. At mimicking logic. But true understanding requires consciousness. Penrose: “It doesn’t make sense to say of a device that it understands something if it’s not even aware of it. There is something much more profound in being conscious of something.” And here’s what should terrify every AI lab on earth. Penrose: “I believe that the brain is following the laws of physics, sure. We don’t have a good picture of the laws of physics.” Penrose: “Quantum mechanics is not an answer to the way the universe operates. It’s a partial answer. It’s incomplete.” We’re trying to engineer synthetic consciousness using classical computation. While biological consciousness likely operates on physics we haven’t even discovered yet. The race to AGI isn’t just an engineering problem. It’s a frontier science problem. The labs are hiring engineers. The problem might require physicists who don’t exist yet.
2:02

Adding more GPUs will never make a machine conscious. Nobel Prize-winning physicist Roger Penrose just dismantled the entire AI race’s core assumption. Right now, the industry operates on one belief. Build massive data centers. Scale the models. AGI will just “wake up.” Penrose destroys this completely. Penrose: “There is this sort of view that once you make a computer complicated enough or something, it suddenly becomes aware. I just don’t believe that. There’s no reason to believe that.” A machine can compute better than any human alive. But computation is not awareness. Penrose: “There is something quite different involved in understanding things, in being aware of things, of feeling things, which is not part of computations.” We’re confusing rule-following with actual intelligence. Penrose: “The keyword is the word ‘understanding.’ You can follow rules alright, but we don’t understand what we’re doing. The understanding is the key point.” Models today are exceptional at processing data. At mimicking logic. But true understanding requires consciousness. Penrose: “It doesn’t make sense to say of a device that it understands something if it’s not even aware of it. There is something much more profound in being conscious of something.” And here’s what should terrify every AI lab on earth. Penrose: “I believe that the brain is following the laws of physics, sure. We don’t have a good picture of the laws of physics.” Penrose: “Quantum mechanics is not an answer to the way the universe operates. It’s a partial answer. It’s incomplete.” We’re trying to engineer synthetic consciousness using classical computation. While biological consciousness likely operates on physics we haven’t even discovered yet. The race to AGI isn’t just an engineering problem. It’s a frontier science problem. The labs are hiring engineers. The problem might require physicists who don’t exist yet.

Dustin

197,015 просмотров • 5 месяцев назад

Roger Penrose, Nobel Prize-winning physicist and mathematician, explains why we should stop calling it AI and start calling it "artificial cleverness": He believes the entire field is mislabelled, and the label itself is doing damage. His objection is simple but cuts deep: "The name is wrong. It's not artificial intelligence. It's not intelligence. Intelligence would involve consciousness. Well, if it's a machine, it's not conscious." For Penrose, people have confused raw computing power with genuine understanding. "People have lost the plot. They've lost it in the power of computing. The thing is that computers have got so powerful that they've lost the thread of what they're doing. But I think consciousness is something different. It's not computational." He believes the term itself has hypnotized people into a category error: "People are so hypnotized. The trouble is that AI is a bad term. It means artificial intelligence. Now intelligence in my view is conscious. That's what intelligence is about." So he proposes a rename. Artificial Cleverness. AC instead of AI. To illustrate the distinction, Penrose draws on his experience teaching mathematics: "You have mathematics students. Some of them understand what they're doing. Some are just clever. They can repeat what they've learned. They know how to do it very cleverly. They can calculate very well, but they don't necessarily understand what they're doing." That gap, between calculating well and actually understanding, is the gap Penrose sees between today's machines and genuine intelligence. Cleverness can be manufactured. Consciousness, in his view, cannot. So the question worth sitting with: when we call a system "intelligent," are we describing what it does, or quietly assuming something about what it is?
1:06

Roger Penrose, Nobel Prize-winning physicist and mathematician, explains why we should stop calling it AI and start calling it "artificial cleverness": He believes the entire field is mislabelled, and the label itself is doing damage. His objection is simple but cuts deep: "The name is wrong. It's not artificial intelligence. It's not intelligence. Intelligence would involve consciousness. Well, if it's a machine, it's not conscious." For Penrose, people have confused raw computing power with genuine understanding. "People have lost the plot. They've lost it in the power of computing. The thing is that computers have got so powerful that they've lost the thread of what they're doing. But I think consciousness is something different. It's not computational." He believes the term itself has hypnotized people into a category error: "People are so hypnotized. The trouble is that AI is a bad term. It means artificial intelligence. Now intelligence in my view is conscious. That's what intelligence is about." So he proposes a rename. Artificial Cleverness. AC instead of AI. To illustrate the distinction, Penrose draws on his experience teaching mathematics: "You have mathematics students. Some of them understand what they're doing. Some are just clever. They can repeat what they've learned. They know how to do it very cleverly. They can calculate very well, but they don't necessarily understand what they're doing." That gap, between calculating well and actually understanding, is the gap Penrose sees between today's machines and genuine intelligence. Cleverness can be manufactured. Consciousness, in his view, cannot. So the question worth sitting with: when we call a system "intelligent," are we describing what it does, or quietly assuming something about what it is?

Big Brain AI

117,990 просмотров • 3 месяцев назад

Can AI become conscious? The argument here is that real thinking is not just computation. Understanding, music, love, and awareness may involve something deeper than what a computer can run. The key point is quantum mechanics. Most physics can be turned into algorithms, but the measurement problem still leaves a gap: something happens that our equations do not fully explain. That is where consciousness may live, in a part of reality that cannot simply be coded. If that is true, AI may get smarter, faster, and more convincing, but still miss the one thing that makes understanding human. Source: YourWeeklyCrew (Youtube) / Writer: Sol
2:40

Can AI become conscious? The argument here is that real thinking is not just computation. Understanding, music, love, and awareness may involve something deeper than what a computer can run. The key point is quantum mechanics. Most physics can be turned into algorithms, but the measurement problem still leaves a gap: something happens that our equations do not fully explain. That is where consciousness may live, in a part of reality that cannot simply be coded. If that is true, AI may get smarter, faster, and more convincing, but still miss the one thing that makes understanding human. Source: YourWeeklyCrew (Youtube) / Writer: Sol

Mario Nawfal

21,114 просмотров • 2 месяцев назад

Sir Roger Penrose argues that current AI is a misnomer because it lacks the one ingredient essential for true intelligence: Understanding. By applying the lens of mathematical logic, he explains that while machines are masters of following rules, the ability to understand why those rules work is a non-computational process. To Penrose, the leap from calculation to comprehension requires more than just better code; it requires Consciousness. At the fundamental level, intelligence isn't just data processing; it's the conscious awareness that gives meaning to the math. Credit: TheInstituteOfArtAndIdeas
0:43

Sir Roger Penrose argues that current AI is a misnomer because it lacks the one ingredient essential for true intelligence: Understanding. By applying the lens of mathematical logic, he explains that while machines are masters of following rules, the ability to understand why those rules work is a non-computational process. To Penrose, the leap from calculation to comprehension requires more than just better code; it requires Consciousness. At the fundamental level, intelligence isn't just data processing; it's the conscious awareness that gives meaning to the math. Credit: TheInstituteOfArtAndIdeas

Cosmos Archive

75,878 просмотров • 6 месяцев назад

The smartest man in AI just exposed the whole AGI narrative as a LIE. And he used a physics problem from 1905 to prove it. His name is Demis Hassabis. He runs Google DeepMind, and won the Nobel Prize for using AI to crack a problem in biology that had stumped scientists for 50 years. Almost nobody in this industry has a track record like his. He went on the NothingButTech podcast and called out the biggest lie in AI right now: Right now the loudest voices in AI are telling you that AGI is basically here. OpenAI has literally defined AGI as a system that can outperform humans at most "economically valuable work." In other words, if it replaces enough jobs, we have arrived. Hassabis thinks that bar is a joke. He said real general intelligence has to do what the human brain can do, because the brain is the only proof we have that this kind of intelligence is even possible. He called that "a higher bar than just being able to do some useful economic work," which is about as close as a polite British Nobel laureate gets to calling his rivals out. Then he gave the actual test: Today's AI has read everything humans have ever written, including the theory of relativity. So when it explains relativity back to you, it's repeating an answer that already exists. That's not intelligence. So Hassabis proposed a test that makes memorization impossible. Train an AI on only what humanity knew in 1901, four years BEFORE Einstein published relativity. Then ask it to come up with relativity on its own. It can't look up the answer, because in 1901 the answer doesn't exist yet. The only way to pass is to do what Einstein actually did: Take the same physics everyone else had and reason its way to an idea no human had ever had. Hassabis says not a single AI today can, no matter how much it has memorized. Which means what we keep calling "almost AGI" is really just the best librarian in history. It can find any answer that already exists but it cannot create one that doesn't. His second version is even sharper: AlphaGo, the system his own team built, famously invented a brand new move that no human had played in 2,000 years of the game. Everyone called it genius but Hassabis says that still is not the bar. The real test is not whether an AI can invent a new move inside Go, it is whether an AI could INVENT a game as deep and as beautiful as Go in the first place. No model that exists today can do it. The people telling you AGI has already arrived are the same people raising hundreds of billions of dollars on that exact promise. The valuations only work if the finish line is right in front of us. So the finish line keeps getting dragged closer, and AGI keeps getting quietly redefined down to "does useful work," until the products they already sell happen to qualify. Hassabis has nothing to prove and nothing to sell you. He already won the Nobel, and he is telling you the machines still cannot do the one thing that would make them genuinely intelligent, which is have a truly original idea. To be fair to him, he is not a pessimist about it. He believes real AGI IS coming, and he is spending his life building it. He just refuses to pretend it is already sitting in your phone. So the next time a founder tells you AGI is months away, remember that the one man in the room with a Nobel Prize built his test around Einstein, and admitted that nothing we have made can pass it. What do you think?
2:45

The smartest man in AI just exposed the whole AGI narrative as a LIE. And he used a physics problem from 1905 to prove it. His name is Demis Hassabis. He runs Google DeepMind, and won the Nobel Prize for using AI to crack a problem in biology that had stumped scientists for 50 years. Almost nobody in this industry has a track record like his. He went on the NothingButTech podcast and called out the biggest lie in AI right now: Right now the loudest voices in AI are telling you that AGI is basically here. OpenAI has literally defined AGI as a system that can outperform humans at most "economically valuable work." In other words, if it replaces enough jobs, we have arrived. Hassabis thinks that bar is a joke. He said real general intelligence has to do what the human brain can do, because the brain is the only proof we have that this kind of intelligence is even possible. He called that "a higher bar than just being able to do some useful economic work," which is about as close as a polite British Nobel laureate gets to calling his rivals out. Then he gave the actual test: Today's AI has read everything humans have ever written, including the theory of relativity. So when it explains relativity back to you, it's repeating an answer that already exists. That's not intelligence. So Hassabis proposed a test that makes memorization impossible. Train an AI on only what humanity knew in 1901, four years BEFORE Einstein published relativity. Then ask it to come up with relativity on its own. It can't look up the answer, because in 1901 the answer doesn't exist yet. The only way to pass is to do what Einstein actually did: Take the same physics everyone else had and reason its way to an idea no human had ever had. Hassabis says not a single AI today can, no matter how much it has memorized. Which means what we keep calling "almost AGI" is really just the best librarian in history. It can find any answer that already exists but it cannot create one that doesn't. His second version is even sharper: AlphaGo, the system his own team built, famously invented a brand new move that no human had played in 2,000 years of the game. Everyone called it genius but Hassabis says that still is not the bar. The real test is not whether an AI can invent a new move inside Go, it is whether an AI could INVENT a game as deep and as beautiful as Go in the first place. No model that exists today can do it. The people telling you AGI has already arrived are the same people raising hundreds of billions of dollars on that exact promise. The valuations only work if the finish line is right in front of us. So the finish line keeps getting dragged closer, and AGI keeps getting quietly redefined down to "does useful work," until the products they already sell happen to qualify. Hassabis has nothing to prove and nothing to sell you. He already won the Nobel, and he is telling you the machines still cannot do the one thing that would make them genuinely intelligent, which is have a truly original idea. To be fair to him, he is not a pessimist about it. He believes real AGI IS coming, and he is spending his life building it. He just refuses to pretend it is already sitting in your phone. So the next time a founder tells you AGI is months away, remember that the one man in the room with a Nobel Prize built his test around Einstein, and admitted that nothing we have made can pass it. What do you think?

Ricardo

1,286,342 просмотров • 2 месяцев назад

Richard Feynman, Nobel Prize-winning physicist: "You can know the name of every pattern in the market and understand nothing about why a single one works. I won a Nobel on that one distinction. it is the whole difference between an edge and a story you tell yourself." this free film is a Nobel laureate teaching you how to actually think, recorded by the BBC and free ever since. at the board it's simple. Feynman's obsession was the gap between naming a thing and understanding it. You can memorize the word for why a stock moved, "momentum", "mean reversion", and still know nothing about whether it will happen again. Real understanding means you can say why, from the mechanism up, and name what would break it. Everything else is a label pasted over ignorance. That's the whole "edge", minus the marketing. Feynman's rule was that the first principle is you must not fool yourself, and you are the easiest person to fool. Same point as my casino piece above: the market is a machine for handing you convincing stories, and the only defense is refusing to believe one you cannot explain. the film is free and anyone can watch it tonight. what nobody can give you is the discipline to admit "I named it but I don't understand it" before you put money on it. That honesty is the edge, and it is the rarest thing there is.
1:06:19

Richard Feynman, Nobel Prize-winning physicist: "You can know the name of every pattern in the market and understand nothing about why a single one works. I won a Nobel on that one distinction. it is the whole difference between an edge and a story you tell yourself." this free film is a Nobel laureate teaching you how to actually think, recorded by the BBC and free ever since. at the board it's simple. Feynman's obsession was the gap between naming a thing and understanding it. You can memorize the word for why a stock moved, "momentum", "mean reversion", and still know nothing about whether it will happen again. Real understanding means you can say why, from the mechanism up, and name what would break it. Everything else is a label pasted over ignorance. That's the whole "edge", minus the marketing. Feynman's rule was that the first principle is you must not fool yourself, and you are the easiest person to fool. Same point as my casino piece above: the market is a machine for handing you convincing stories, and the only defense is refusing to believe one you cannot explain. the film is free and anyone can watch it tonight. what nobody can give you is the discipline to admit "I named it but I don't understand it" before you put money on it. That honesty is the edge, and it is the rarest thing there is.

Rossst.03

20,025 просмотров • 1 месяц назад

"It’s not AI; it’s AC; Artificial Cleverness!" Sir Roger Penrose explains why current "Artificial Intelligence" is missing the most critical ingredient: consciousness. By delving into the limits of mathematical computability, he argues that while computers are masters of "computational mathematics," true intelligence requires a conscious understanding that exists beyond any algorithm. At the fundamental level, what we call AI is just high-speed calculation. To Penrose, intelligence and consciousness are inseparable; and until a machine can "understand," it’s simply being clever.
0:52

"It’s not AI; it’s AC; Artificial Cleverness!" Sir Roger Penrose explains why current "Artificial Intelligence" is missing the most critical ingredient: consciousness. By delving into the limits of mathematical computability, he argues that while computers are masters of "computational mathematics," true intelligence requires a conscious understanding that exists beyond any algorithm. At the fundamental level, what we call AI is just high-speed calculation. To Penrose, intelligence and consciousness are inseparable; and until a machine can "understand," it’s simply being clever.

Cosmos Archive

83,200 просмотров • 5 месяцев назад

THE MAN WHO WROTE THE ONE ESSAY EVERY AI LAB TREATS AS SCRIPTURE NOW SAYS THE THING THEY BUILT WITH IT IS A DEAD END. THE FATHER OF THE "JUST SCALE IT" GOSPEL IS TELLING YOU THAT STACKING MORE LLMs LEADS NOWHERE 67 minutes with Richard Sutton -- father of reinforcement learning and winner of the 2024 Turing Award, the highest honor in computer science. -> His argument: an LLM only ever learns from human text. It imitates what people already wrote, but it never learns a single thing from its own experience of the world. A squirrel, a baby, even a rat learns on the job -- try something, see what happens, update. An LLM finishes training and then it is frozen. It cannot actually learn from you. So no matter how much compute you pour in, you are scaling a better and better imitator, not something that understands. The ceiling is baked in. The brutal part: everyone quotes his "Bitter Lesson" to justify the scaling race. He says they misread him -- real intelligence comes from learning through experience, and that piece is still completely missing. You assumed bigger models were the road to real AI. This is the father of the field telling you it is the wrong one. Save this. It is the bear case straight from the source ↓
1:06:59

THE MAN WHO WROTE THE ONE ESSAY EVERY AI LAB TREATS AS SCRIPTURE NOW SAYS THE THING THEY BUILT WITH IT IS A DEAD END. THE FATHER OF THE "JUST SCALE IT" GOSPEL IS TELLING YOU THAT STACKING MORE LLMs LEADS NOWHERE 67 minutes with Richard Sutton -- father of reinforcement learning and winner of the 2024 Turing Award, the highest honor in computer science. -> His argument: an LLM only ever learns from human text. It imitates what people already wrote, but it never learns a single thing from its own experience of the world. A squirrel, a baby, even a rat learns on the job -- try something, see what happens, update. An LLM finishes training and then it is frozen. It cannot actually learn from you. So no matter how much compute you pour in, you are scaling a better and better imitator, not something that understands. The ceiling is baked in. The brutal part: everyone quotes his "Bitter Lesson" to justify the scaling race. He says they misread him -- real intelligence comes from learning through experience, and that piece is still completely missing. You assumed bigger models were the road to real AI. This is the father of the field telling you it is the wrong one. Save this. It is the bear case straight from the source ↓

slash1s

12,799 просмотров • 1 месяц назад

Francis Atwoli: After Raila Odinga, there is no opposition in Kenya. Kalonzo Musyoka is a good man and it is I who told Raila to let Kalonzo Musyoka be the leader of the opposition. This is a good man, he is a diplomat, he is a person who can be a priest, he can be a person who can pray for anybody, he is a man that you can trust with whatever you have. But he is not best suited to say that he is the person who can be the leader of the opposition in this country. If Kenyans want, he can be the president #JKLive
1:10

Francis Atwoli: After Raila Odinga, there is no opposition in Kenya. Kalonzo Musyoka is a good man and it is I who told Raila to let Kalonzo Musyoka be the leader of the opposition. This is a good man, he is a diplomat, he is a person who can be a priest, he can be a person who can pray for anybody, he is a man that you can trust with whatever you have. But he is not best suited to say that he is the person who can be the leader of the opposition in this country. If Kenyans want, he can be the president #JKLive

Citizen TV Kenya

86,905 просмотров • 7 месяцев назад

AP’s Zeke Miller: “And you’ve also said several times that the President would not pardon or commute the sentences for his son, Hunter. I just want to make sure that that is not going to change over the next six months. The President's saying that he will not —” KJP: “It’s still — it’s still — it’s still a no. It’s still a no.” Miller: “It will always be no?” KJP: “It is a no. It will be a no. It is a no, and I don't have anything else to add. Will he pardon his son? No.” Miller: “Thank you.”
0:25

AP’s Zeke Miller: “And you’ve also said several times that the President would not pardon or commute the sentences for his son, Hunter. I just want to make sure that that is not going to change over the next six months. The President's saying that he will not —” KJP: “It’s still — it’s still — it’s still a no. It’s still a no.” Miller: “It will always be no?” KJP: “It is a no. It will be a no. It is a no, and I don't have anything else to add. Will he pardon his son? No.” Miller: “Thank you.”

Curtis Houck

54,545 просмотров • 2 лет назад

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓
43:30

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

slash1s

22,107 просмотров • 2 месяцев назад

––Charlie Barnett: "Consciousness and the computability of it. It sounds like, or at least in the past, that you've implied that consciousness is computable. Some, like Roger Penrose, have argued the opposite, and he's argued that consciousness is non-computational, and he uses Gödel's incompleteness theorems to argue that the mind can see truths that a purely algorithmic system can't derive, and therefore the brain must be using some kind of non-computable process when it comes to consciousness, something beyond what machines can do. What would you say to a view like that? David Deutsch: Yet again, it is using an impossible conception of what knowledge is. So Penrose thinks that when we see a proof of a mathematical theorem, we are touching certainty, we are god-like entities when we're mathematicians. But that's not true. Our mathematical knowledge is conjectural, just like our knowledge of physics. It's even more removed from our senses, because it's not true that the interior of our brains and the interior of our thoughts is more accessible to us than the world we perceive through our senses, or the world that we perceive through our theories, the center of the sun. We know lots about the center of the sun, even though no one has ever perceived it, and perhaps no one ever will. So mathematical truths are based on conjecture. What Gödel showed is that there is no firm ground underneath mathematical theories either. There's no way of proving that the standards of proof that we currently use are perfectly rigorous. And there have been cases in history where they have shown not to be rigorous. I think Pernot, who was the first to axiomatize the principles of the natural numbers, his first attempt at that was wrong. And it's interesting that he did not say, well, I've axiomatized them, therefore there's nothing to them other than my axioms. No, he said, oh dear, my axioms don't correctly represent the real number, the natural numbers, so I have to change them. So he was grasping, conjecturing for a reality, an abstract reality, just like scientists try to grasp physical reality. So the same epistemology applies to mathematics as it does to science."
2:31

––Charlie Barnett: "Consciousness and the computability of it. It sounds like, or at least in the past, that you've implied that consciousness is computable. Some, like Roger Penrose, have argued the opposite, and he's argued that consciousness is non-computational, and he uses Gödel's incompleteness theorems to argue that the mind can see truths that a purely algorithmic system can't derive, and therefore the brain must be using some kind of non-computable process when it comes to consciousness, something beyond what machines can do. What would you say to a view like that? David Deutsch: Yet again, it is using an impossible conception of what knowledge is. So Penrose thinks that when we see a proof of a mathematical theorem, we are touching certainty, we are god-like entities when we're mathematicians. But that's not true. Our mathematical knowledge is conjectural, just like our knowledge of physics. It's even more removed from our senses, because it's not true that the interior of our brains and the interior of our thoughts is more accessible to us than the world we perceive through our senses, or the world that we perceive through our theories, the center of the sun. We know lots about the center of the sun, even though no one has ever perceived it, and perhaps no one ever will. So mathematical truths are based on conjecture. What Gödel showed is that there is no firm ground underneath mathematical theories either. There's no way of proving that the standards of proof that we currently use are perfectly rigorous. And there have been cases in history where they have shown not to be rigorous. I think Pernot, who was the first to axiomatize the principles of the natural numbers, his first attempt at that was wrong. And it's interesting that he did not say, well, I've axiomatized them, therefore there's nothing to them other than my axioms. No, he said, oh dear, my axioms don't correctly represent the real number, the natural numbers, so I have to change them. So he was grasping, conjecturing for a reality, an abstract reality, just like scientists try to grasp physical reality. So the same epistemology applies to mathematics as it does to science."

Deutsch Explains

13,826 просмотров • 1 год назад

“The simplest acts of kindness are by far more powerful than a thousand heads bowing in prayer.” Day after day, #Sebaashray2 proves that kindness is not a ritual, not a performance, not a staged promise, it is a force that walks straight into the lives of the people. You can hear it in the steady hum of service that refuses to pause, even for a moment. Sebaashray is not just an initiative, it is a reminder that governance can have a heartbeat. That care can be limitless. That compassion can be organised, disciplined, and unshakeable. Wherever it reaches, it leaves behind a simple truth: dignity is not charity, and service is not sympathy. It is responsibility. It is duty. And it is the moral compass that guides this mission every single day. In each lane, under every tent, across every queue, Sebaashray embodies what true public service must look like: quiet, constant, and deeply human.
1:17

“The simplest acts of kindness are by far more powerful than a thousand heads bowing in prayer.” Day after day, #Sebaashray2 proves that kindness is not a ritual, not a performance, not a staged promise, it is a force that walks straight into the lives of the people. You can hear it in the steady hum of service that refuses to pause, even for a moment. Sebaashray is not just an initiative, it is a reminder that governance can have a heartbeat. That care can be limitless. That compassion can be organised, disciplined, and unshakeable. Wherever it reaches, it leaves behind a simple truth: dignity is not charity, and service is not sympathy. It is responsibility. It is duty. And it is the moral compass that guides this mission every single day. In each lane, under every tent, across every queue, Sebaashray embodies what true public service must look like: quiet, constant, and deeply human.

Abhishek Banerjee

253,697 просмотров • 8 месяцев 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."
3:11

.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

72,455 просмотров • 1 год назад

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.
0:59

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.

hoe_math = PsychoMath

1,189,824 просмотров • 11 месяцев назад

Same credit score. Same symptoms. But if you are Black, the AI says no. NAZI SCUMBAG #ElonMusk is in federal court right now fighting to keep it that way. Colorado passed a law: If you build AI that makes decisions about people’s housing, their jobs, or their healthcare, that AI has to be fair. That is the entire law. Musk filed a federal lawsuit to block it. His argument? Forcing his AI not to discriminate violates his First Amendment rights. Read that again. He is arguing in federal court that “do not discriminate against Black people” is a political opinion he should not have to follow. Never forget that Musk is all over the #EpsteinFiles.
1:14

Same credit score. Same symptoms. But if you are Black, the AI says no. NAZI SCUMBAG #ElonMusk is in federal court right now fighting to keep it that way. Colorado passed a law: If you build AI that makes decisions about people’s housing, their jobs, or their healthcare, that AI has to be fair. That is the entire law. Musk filed a federal lawsuit to block it. His argument? Forcing his AI not to discriminate violates his First Amendment rights. Read that again. He is arguing in federal court that “do not discriminate against Black people” is a political opinion he should not have to follow. Never forget that Musk is all over the #EpsteinFiles.

TasetiReloaded2 🇧🇫🇳🇪🇲🇱🔴⚫️🟢

23,550 просмотров • 4 месяцев назад

On a scale of no big deal to I would not be in that house How bad is this The inspector in comments says that the beam is NOT imbedded in the concrete walls - he can put his fingers behind it at the wall
0:40

On a scale of no big deal to I would not be in that house How bad is this The inspector in comments says that the beam is NOT imbedded in the concrete walls - he can put his fingers behind it at the wall

Julie Chang

323,610 просмотров • 1 год назад

Richard Feynman, Nobel Prize-winning physicist: "The universe itself doesn't know what happens next. it only knows the odds. I won a Nobel proving reality runs on probability, not certainty, which means the casino isn't cheating you. it's just closer to how nature works than you are." this free lecture from 1964 is a Nobel laureate explaining that certainty is not something the universe offers, and it has been public for sixty years. at the board it's simple. Feynman showed that at the deepest level nature does not decide what will happen, only the probability of what might. Fire a single electron at two slits and no one alive can tell you where it lands, only the odds of each spot. This drove Einstein to say God does not play dice. Feynman and the experiments proved him wrong. Reality is a probability machine, all the way down. That's the whole thing, minus the mysticism. Which means the casino is not an exception to how the world works. It is a scale model of it. Nobody gets certainty, not the gambler, not the trader, not the universe. Same point as my article above: the house wins not because it knows the outcome, but because it prices the odds while you chase a sure thing that does not exist anywhere in nature. the physics is free and it has been settled for a century. what nobody can sell you is the discipline to give up the craving for certainty and act on probabilities instead. That surrender is the whole edge, and it is the hardest thing a human mind ever does.
53:34

Richard Feynman, Nobel Prize-winning physicist: "The universe itself doesn't know what happens next. it only knows the odds. I won a Nobel proving reality runs on probability, not certainty, which means the casino isn't cheating you. it's just closer to how nature works than you are." this free lecture from 1964 is a Nobel laureate explaining that certainty is not something the universe offers, and it has been public for sixty years. at the board it's simple. Feynman showed that at the deepest level nature does not decide what will happen, only the probability of what might. Fire a single electron at two slits and no one alive can tell you where it lands, only the odds of each spot. This drove Einstein to say God does not play dice. Feynman and the experiments proved him wrong. Reality is a probability machine, all the way down. That's the whole thing, minus the mysticism. Which means the casino is not an exception to how the world works. It is a scale model of it. Nobody gets certainty, not the gambler, not the trader, not the universe. Same point as my article above: the house wins not because it knows the outcome, but because it prices the odds while you chase a sure thing that does not exist anywhere in nature. the physics is free and it has been settled for a century. what nobody can sell you is the discipline to give up the craving for certainty and act on probabilities instead. That surrender is the whole edge, and it is the hardest thing a human mind ever does.

Voltex

10,875 просмотров • 1 месяц назад

I don’t care what anyone says this is an incredible moment. And you can say whatever you want about President Trump, but you can never say that he does not love this country. Or that he’s not proud of it. He is and he shows that to the world and I for one love to see that instead of the apology tours.
1:53

I don’t care what anyone says this is an incredible moment. And you can say whatever you want about President Trump, but you can never say that he does not love this country. Or that he’s not proud of it. He is and he shows that to the world and I for one love to see that instead of the apology tours.

Insurrection Barbie

102,926 просмотров • 1 год назад

Steve Jobs on why everything around you was made by people no smarter than you: "When you grow up, you tend to get told that the world is the way it is and your life is just to live your life inside the world. Try not to bash into the walls too much, have a nice family life, have fun, save a little money. But that's a very limited life." Steve believed most people live with a fundamental misconception. As he puts it: "Life can be much broader once you discover one simple fact. And that is—everything around you that you call life was made up by people that were no smarter than you." He continues: "And you can change it. You can influence it. You can build your own things that other people can use. And the minute that you understand that you can poke life and actually something will pop out the other side—that you can change it, you can mold it." On what matters most: "Maybe the most important thing is to shake off this erroneous notion that life is there and you're just going to live in it versus embrace it, change it, improve it, make your mark upon it. I think that's very important." His perspective on why you should change things: "However you learn that, once you learn it, you'll want to change life and make it better because it's kind of messed up in a lot of ways." The shift: "Once you learn that, you'll never be the same again."
1:28

Steve Jobs on why everything around you was made by people no smarter than you: "When you grow up, you tend to get told that the world is the way it is and your life is just to live your life inside the world. Try not to bash into the walls too much, have a nice family life, have fun, save a little money. But that's a very limited life." Steve believed most people live with a fundamental misconception. As he puts it: "Life can be much broader once you discover one simple fact. And that is—everything around you that you call life was made up by people that were no smarter than you." He continues: "And you can change it. You can influence it. You can build your own things that other people can use. And the minute that you understand that you can poke life and actually something will pop out the other side—that you can change it, you can mold it." On what matters most: "Maybe the most important thing is to shake off this erroneous notion that life is there and you're just going to live in it versus embrace it, change it, improve it, make your mark upon it. I think that's very important." His perspective on why you should change things: "However you learn that, once you learn it, you'll want to change life and make it better because it's kind of messed up in a lot of ways." The shift: "Once you learn that, you'll never be the same again."

Jaynit

48,518 просмотров • 7 месяцев назад