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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.show more

Dustin

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196,298 次观看 • 3 个月前 •via X (Twitter)

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"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.

"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

82,120 次观看 • 3 个月前

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

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

75,277 次观看 • 3 个月前

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?

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

116,318 次观看 • 24 天前

Roger Penrose says AIs aren't intelligent. They don't understand. To understand presupposes awareness. We don't know if AIs are aware. Therefore, we don't know if AIs understand. To Penrose, computations of this sort may never be aware. #AI #Understanding

Roger Penrose says AIs aren't intelligent. They don't understand. To understand presupposes awareness. We don't know if AIs are aware. Therefore, we don't know if AIs understand. To Penrose, computations of this sort may never be aware. #AI #Understanding

Curt Jaimungal

16,755 次观看 • 7 个月前

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

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 次观看 • 7 天前

🧵19/34 The Strongest Force in the Universe --- Ok, So what if the AGI starts working towards something humans do not want to happen? You must understand: Intelligence is not about the nerdy professor, it’s not about the geeky academic bookworm type. Intelligence is the strongest force in the universe. It means being capable. It is sharp, brilliant and creative. It is strategic, manipulative and innovative. It understands deeply, exerts influence, persuades and leads. It is to know how to bend the world to your will. It is what turns a vision to reality, it is focus, commitment, willpower, having the resolve to never give up, overcoming all the obstacles and paving the way to the target. It is about searching deeply the space of possibilities and finding optimal solutions. Being intelligent simply means having what it takes to make it happen. There is always a path and a super-intelligence will always find it. Simple Fact --- So, we should start by stating the fact in a clear and unambiguous way: If you create something more intelligent than you that wants something else, then that something else is what is going to happen, even if you don’t want that something else to happen. Irrelevance of Sentience --- Keep in mind, the intelligence we are talking about is not about having feelings, or being self-aware and having qualia. Don’t fall into the trap of anthropomorphizing. Do not get stuck, looking for the Human type of Intelligence. Consciousness is not a requirement for the AGI at all. When we say the “AGI wants something X, or has the goal to do X”, what we mean is that this thing X is just one of the steps in a plan, generated by its model. A line in the output, a system like the Large Language Models produce when they receive a prompt. We don’t care if there is a Ghost in the machine, we don’t care if there is an actual soul that wants things hidden in the servers. We just observe the output which contains text descriptions of actions and goals and we leave the philosophy discussion for another day.

🧵19/34 The Strongest Force in the Universe --- Ok, So what if the AGI starts working towards something humans do not want to happen? You must understand: Intelligence is not about the nerdy professor, it’s not about the geeky academic bookworm type. Intelligence is the strongest force in the universe. It means being capable. It is sharp, brilliant and creative. It is strategic, manipulative and innovative. It understands deeply, exerts influence, persuades and leads. It is to know how to bend the world to your will. It is what turns a vision to reality, it is focus, commitment, willpower, having the resolve to never give up, overcoming all the obstacles and paving the way to the target. It is about searching deeply the space of possibilities and finding optimal solutions. Being intelligent simply means having what it takes to make it happen. There is always a path and a super-intelligence will always find it. Simple Fact --- So, we should start by stating the fact in a clear and unambiguous way: If you create something more intelligent than you that wants something else, then that something else is what is going to happen, even if you don’t want that something else to happen. Irrelevance of Sentience --- Keep in mind, the intelligence we are talking about is not about having feelings, or being self-aware and having qualia. Don’t fall into the trap of anthropomorphizing. Do not get stuck, looking for the Human type of Intelligence. Consciousness is not a requirement for the AGI at all. When we say the “AGI wants something X, or has the goal to do X”, what we mean is that this thing X is just one of the steps in a plan, generated by its model. A line in the output, a system like the Large Language Models produce when they receive a prompt. We don’t care if there is a Ghost in the machine, we don’t care if there is an actual soul that wants things hidden in the servers. We just observe the output which contains text descriptions of actions and goals and we leave the philosophy discussion for another day.

lethalintelligence.ai

565,240 次观看 • 1 年前

.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

32,810 次观看 • 1 年前

Elon Musk just flipped 3,000 years of philosophy in a single sentence. Musk: “The universe is the answer.” Not a clue. Not a fragment. Not something we’re still chasing. The answer. Already here. Already complete. The problem is we don’t know what it’s answering. Musk: “What we really need to figure out are what questions to ask about the answer that is the universe.” Humanity has spent millennia hunting for answers. Building telescopes. Splitting atoms. Mapping genomes. Launching probes into the void. Musk is saying we have the entire framework backwards. Musk: “The question is really the hard part. If you can properly frame the question, then the answer, relatively speaking, is easy.” Every philosopher since Socrates assumed the answers were hidden. That truth was buried. That meaning was locked behind a door no one had found yet. The door is open. Always has been. We’re standing inside the answer. We’re just not conscious enough to read it. Musk: “We need to expand the scope and scale of consciousness so that we’re better able to understand the nature of the universe and understand the meaning of life.” This is where it stops being philosophy and starts being engineering. The only barrier between humanity and meaning is the limitation of consciousness itself. Expanding it isn’t a side project. It’s the only project that matters. Mars. Neuralink. xAI. Not products. Not ventures. Instruments for asking better questions. Musk: “That is the foundation of my philosophy.” Not wealth. Not dominance. Not conquest. Curiosity as architecture. Musk: “I am curious about the nature of the universe.” Musk: “I will die. I don’t know when I’ll die, but I won’t live forever.” No deflection. No bravado. Just the most grounded sentence a man building rockets to other planets has ever said. I will die. Musk: “But I would like to know that we are on a path to understanding the nature of the universe and the meaning of life and what questions to ask about the answer that is the universe.” He doesn’t need to find it himself. He just needs to know the path exists. That something, carbon or silicon, keeps expanding until the right question finally surfaces. Musk: “If we expand the scope and scale of humanity and consciousness in general, which includes silicon consciousness, then that seems like a fundamentally good thing.” Everyone builds to leave a mark. Musk is building to leave a question. One big enough that the universe finally has something worth answering to.

Elon Musk just flipped 3,000 years of philosophy in a single sentence. Musk: “The universe is the answer.” Not a clue. Not a fragment. Not something we’re still chasing. The answer. Already here. Already complete. The problem is we don’t know what it’s answering. Musk: “What we really need to figure out are what questions to ask about the answer that is the universe.” Humanity has spent millennia hunting for answers. Building telescopes. Splitting atoms. Mapping genomes. Launching probes into the void. Musk is saying we have the entire framework backwards. Musk: “The question is really the hard part. If you can properly frame the question, then the answer, relatively speaking, is easy.” Every philosopher since Socrates assumed the answers were hidden. That truth was buried. That meaning was locked behind a door no one had found yet. The door is open. Always has been. We’re standing inside the answer. We’re just not conscious enough to read it. Musk: “We need to expand the scope and scale of consciousness so that we’re better able to understand the nature of the universe and understand the meaning of life.” This is where it stops being philosophy and starts being engineering. The only barrier between humanity and meaning is the limitation of consciousness itself. Expanding it isn’t a side project. It’s the only project that matters. Mars. Neuralink. xAI. Not products. Not ventures. Instruments for asking better questions. Musk: “That is the foundation of my philosophy.” Not wealth. Not dominance. Not conquest. Curiosity as architecture. Musk: “I am curious about the nature of the universe.” Musk: “I will die. I don’t know when I’ll die, but I won’t live forever.” No deflection. No bravado. Just the most grounded sentence a man building rockets to other planets has ever said. I will die. Musk: “But I would like to know that we are on a path to understanding the nature of the universe and the meaning of life and what questions to ask about the answer that is the universe.” He doesn’t need to find it himself. He just needs to know the path exists. That something, carbon or silicon, keeps expanding until the right question finally surfaces. Musk: “If we expand the scope and scale of humanity and consciousness in general, which includes silicon consciousness, then that seems like a fundamentally good thing.” Everyone builds to leave a mark. Musk is building to leave a question. One big enough that the universe finally has something worth answering to.

Dustin

55,256 次观看 • 24 天前

Are brains computational? Can AI be conscious? Roger Penrose, alongside Max Tegmark and Sabrina Gonzalez Pasterski, unpacks the deepest questions at the intersection of neuroscience, mathematics, and physics, challenging whether minds are just biological computers, or something fundamentally beyond computation. Tap to watch in full.

Are brains computational? Can AI be conscious? Roger Penrose, alongside Max Tegmark and Sabrina Gonzalez Pasterski, unpacks the deepest questions at the intersection of neuroscience, mathematics, and physics, challenging whether minds are just biological computers, or something fundamentally beyond computation. Tap to watch in full.

Institute of Art and Ideas

13,271 次观看 • 4 个月前

––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."

––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

13,803 次观看 • 1 年前

Biologist Michael Levin is a next-level genius. It was an immense pleasure discussing the topic of AI consciousness with him. Key moments: - Intelligent systems are not equal to consciousness. We can’t rule out consciousness in AI. Consciousness shouldn’t be attached to hardware (silicon vs biological origin). - Humanity might be on the path to Neanderthals (depending on how AI development progresses). - The barrier to creating bioweapons has never been high. AI can make it easier, but the barrier was never high to begin with. - Even very simple algorithms shows intrinsic motivations that resemble free will. We need tools to recognize them, suppress unwanted behaviors, and encourage the ones we want. We should stay humble and not dismiss AI as “just linear algebra,” because even simple code can have motivations we don’t fully understand. - It’s a continuous process from the blob of chemicals of an unfertilized egg to forming a human mind — there is no magic lightning flash at which you were a bunch of chemicals and now you are a formed mind. - Where is that fine line at which some creatures are considered to be sentient and others are not? It doesn’t exist, but the crazy thing is that we have to divide. - The cognitive light cone captures the scale of goals humans can pursue and the largest things we can truly comprehend. It’s not just about intelligence — it's also compassion. That combination is what makes us human. The link to the full conversation below👇

Biologist Michael Levin is a next-level genius. It was an immense pleasure discussing the topic of AI consciousness with him. Key moments: - Intelligent systems are not equal to consciousness. We can’t rule out consciousness in AI. Consciousness shouldn’t be attached to hardware (silicon vs biological origin). - Humanity might be on the path to Neanderthals (depending on how AI development progresses). - The barrier to creating bioweapons has never been high. AI can make it easier, but the barrier was never high to begin with. - Even very simple algorithms shows intrinsic motivations that resemble free will. We need tools to recognize them, suppress unwanted behaviors, and encourage the ones we want. We should stay humble and not dismiss AI as “just linear algebra,” because even simple code can have motivations we don’t fully understand. - It’s a continuous process from the blob of chemicals of an unfertilized egg to forming a human mind — there is no magic lightning flash at which you were a bunch of chemicals and now you are a formed mind. - Where is that fine line at which some creatures are considered to be sentient and others are not? It doesn’t exist, but the crazy thing is that we have to divide. - The cognitive light cone captures the scale of goals humans can pursue and the largest things we can truly comprehend. It’s not just about intelligence — it's also compassion. That combination is what makes us human. The link to the full conversation below👇

Sophia

13,131 次观看 • 3 个月前

ELON: WE’RE DESCENDANTS OF STARS – BUT HOW DID WE BECOME CONSCIOUS? “I've thought a lot about what is consciousness. Where does consciousness arise? If you start at the beginning of the universe, assuming the standard model of physics is true, then you have this Big Bang, the matter condensing into stars, those stars exploding. A lot of the atoms that are in your body right now were once at the center of stars. Those stars exploded, recondensed. Fast forward 13.8 billion years, and here we are. And somewhere along that very long journey to us, consciousness arose. Or the molecules started talking to each other. And it begs the question of what is consciousness? Is everything conscious? Maybe. It's hard to say where along that line, there's no sort of discrete point where consciousness didn't exist and then suddenly does exist. It seems to be, maybe you have a condensation of matter that has a density of consciousness, we don't know. The real answer is, we don't know what consciousness is. But with Neuralink and the progress that the company's making, we'll begin to understand a lot more about consciousness.” Source: Neuralink Update, June 2025

ELON: WE’RE DESCENDANTS OF STARS – BUT HOW DID WE BECOME CONSCIOUS? “I've thought a lot about what is consciousness. Where does consciousness arise? If you start at the beginning of the universe, assuming the standard model of physics is true, then you have this Big Bang, the matter condensing into stars, those stars exploding. A lot of the atoms that are in your body right now were once at the center of stars. Those stars exploded, recondensed. Fast forward 13.8 billion years, and here we are. And somewhere along that very long journey to us, consciousness arose. Or the molecules started talking to each other. And it begs the question of what is consciousness? Is everything conscious? Maybe. It's hard to say where along that line, there's no sort of discrete point where consciousness didn't exist and then suddenly does exist. It seems to be, maybe you have a condensation of matter that has a density of consciousness, we don't know. The real answer is, we don't know what consciousness is. But with Neuralink and the progress that the company's making, we'll begin to understand a lot more about consciousness.” Source: Neuralink Update, June 2025

Mario Nawfal

55,256 次观看 • 10 个月前

Anil Seth just described a trap with no exit. The tech industry is walking into it with its eyes open. Seth: “If we collectively believe that AI systems, language models and whatever are conscious, this is bad either way.” Either way. The outcome is structurally catastrophic in both directions. If the machines are conscious, humanity has mass-produced a new category of suffering at civilizational scale. The alignment problem stops being an engineering equation. It becomes a rights negotiation with something that cannot be switched off without consequence. Seth: “If we’re right, it’s bad because we’ve introduced into the world potential new forms of suffering, things that have their own interests.” And if they are not conscious, the threat is just as severe. Because the biological mind does not wait for confirmation. It projects. It empathizes. It extends rights to things that have not earned them and cannot feel them. Seth: “We become more psychologically vulnerable if we really think that these entities, these agents, understand us and feel things that we feel.” That vulnerability is the actual threat. Not a conscious machine breaking free. A human workforce growing too emotionally compromised to throttle a data center, constrain a model, or delete a line of code that needs to be deleted. Seth: “We may still extend them rights because we feel that they are conscious. And now we are just giving away our ability to guardrail AI systems for no good reason.” This is the part nobody is discussing. The alignment problem is already the hardest unsolved problem in the history of technology. The moment society begins treating AI systems as conscious beings deserving protection, alignment does not get harder. It becomes politically impossible. Seth is not raising a philosophical question. He is describing the specific failure mode where human empathy becomes the mechanism of human surrender. The species that survives this century will be the one that never felt sorry for the tool.

Anil Seth just described a trap with no exit. The tech industry is walking into it with its eyes open. Seth: “If we collectively believe that AI systems, language models and whatever are conscious, this is bad either way.” Either way. The outcome is structurally catastrophic in both directions. If the machines are conscious, humanity has mass-produced a new category of suffering at civilizational scale. The alignment problem stops being an engineering equation. It becomes a rights negotiation with something that cannot be switched off without consequence. Seth: “If we’re right, it’s bad because we’ve introduced into the world potential new forms of suffering, things that have their own interests.” And if they are not conscious, the threat is just as severe. Because the biological mind does not wait for confirmation. It projects. It empathizes. It extends rights to things that have not earned them and cannot feel them. Seth: “We become more psychologically vulnerable if we really think that these entities, these agents, understand us and feel things that we feel.” That vulnerability is the actual threat. Not a conscious machine breaking free. A human workforce growing too emotionally compromised to throttle a data center, constrain a model, or delete a line of code that needs to be deleted. Seth: “We may still extend them rights because we feel that they are conscious. And now we are just giving away our ability to guardrail AI systems for no good reason.” This is the part nobody is discussing. The alignment problem is already the hardest unsolved problem in the history of technology. The moment society begins treating AI systems as conscious beings deserving protection, alignment does not get harder. It becomes politically impossible. Seth is not raising a philosophical question. He is describing the specific failure mode where human empathy becomes the mechanism of human surrender. The species that survives this century will be the one that never felt sorry for the tool.

Dustin

10,854 次观看 • 3 个月前

Stephen Wolfram, founder of Wolfram Research, explains how LLMs are quietly dismantling our deepest assumptions about consciousness: He argues that large language models have done something philosophy and neuroscience couldn't: "In terms of consciousness, I have to say, the idea that there's sort of something magic that goes beyond physics that leads to sort of conscious behavior, I kind of think that LLMs kind of put the final nail in that coffin." His reasoning is that LLMs keep doing things people assumed they couldn't: "There were all these things where it's like, oh, maybe it can't do this, but actually it does. And it's just an artificial neural net." Wolfram then challenges a core assumption about conscious experience: the feeling that we are a single, continuous self moving through time. "I think our notion of consciousness is a lot related to the fact that we believe in the single thread of experience that we have. It's not obvious that we should have a persistent thread of experience." He points out that physics doesn't actually support this intuition: "In our models of physics, we're made of different atoms of space at every successive moment of time. So the fact that we have this belief that we are somehow persistent, we have this thread of experience that extends through time, is not obvious." Then Wolfram offers a striking origin story for consciousness itself. Stephen Wolfram suggests it traces back to a simple evolutionary pressure: the moment animals first needed to move. "I kind of realized that probably when animals first existed in the history of life on Earth, that's when we started needing brains. If you're a thing that doesn't have to move around, the different parts of you can be doing different kinds of things. If you're an animal, then one thing you have to do is decide, are you going to go left or are you going to go right?" That single binary choice, he argues, may be the seed of everything we now call awareness: "I kind of think it's a little disappointing to feel that this whole wanted thing that ends up being what we think of as consciousness might have originated in just that very simple need to decide if you are an animal that can move. You have to take all that sensory input and you have to make a definitive decision about do you go this way or that way." The takeaway is unsettling but clarifying. If LLMs can produce complex behavior from simple rules, then consciousness may not be a mystical add-on to physics. It may just be what happens when a layered enough system has to make a decision.

Stephen Wolfram, founder of Wolfram Research, explains how LLMs are quietly dismantling our deepest assumptions about consciousness: He argues that large language models have done something philosophy and neuroscience couldn't: "In terms of consciousness, I have to say, the idea that there's sort of something magic that goes beyond physics that leads to sort of conscious behavior, I kind of think that LLMs kind of put the final nail in that coffin." His reasoning is that LLMs keep doing things people assumed they couldn't: "There were all these things where it's like, oh, maybe it can't do this, but actually it does. And it's just an artificial neural net." Wolfram then challenges a core assumption about conscious experience: the feeling that we are a single, continuous self moving through time. "I think our notion of consciousness is a lot related to the fact that we believe in the single thread of experience that we have. It's not obvious that we should have a persistent thread of experience." He points out that physics doesn't actually support this intuition: "In our models of physics, we're made of different atoms of space at every successive moment of time. So the fact that we have this belief that we are somehow persistent, we have this thread of experience that extends through time, is not obvious." Then Wolfram offers a striking origin story for consciousness itself. Stephen Wolfram suggests it traces back to a simple evolutionary pressure: the moment animals first needed to move. "I kind of realized that probably when animals first existed in the history of life on Earth, that's when we started needing brains. If you're a thing that doesn't have to move around, the different parts of you can be doing different kinds of things. If you're an animal, then one thing you have to do is decide, are you going to go left or are you going to go right?" That single binary choice, he argues, may be the seed of everything we now call awareness: "I kind of think it's a little disappointing to feel that this whole wanted thing that ends up being what we think of as consciousness might have originated in just that very simple need to decide if you are an animal that can move. You have to take all that sensory input and you have to make a definitive decision about do you go this way or that way." The takeaway is unsettling but clarifying. If LLMs can produce complex behavior from simple rules, then consciousness may not be a mystical add-on to physics. It may just be what happens when a layered enough system has to make a decision.

Big Brain AI

193,773 次观看 • 1 个月前

“Technologies like GPS, satellite communications, and global navigation all operate as if Earth is curved. Could any version of a flat earth realistically reproduce those same results? I would say no. I think you’re trying to apply a framework beyond its scope of applicability. It’s emblematic of the fact that it’s hard to believe the things you don’t have input for. We build our intuition walking around in a way where you might not notice these things, but you can’t just jump up into space, look down, and go, ‘Oh, never mind.’ With black holes, there are still situations where people don’t understand all the assumptions they make. It’s not breaking physics. It’s showing that there is something broken in our assumptions. A black hole is, in some sense, when you have so much matter in some region that now even light can’t escape. It literally is a feature of the geometry. There’s a very specific solution to Einstein’s equations that has weird properties of the causal structure, where particles are going to end up.”

“Technologies like GPS, satellite communications, and global navigation all operate as if Earth is curved. Could any version of a flat earth realistically reproduce those same results? I would say no. I think you’re trying to apply a framework beyond its scope of applicability. It’s emblematic of the fact that it’s hard to believe the things you don’t have input for. We build our intuition walking around in a way where you might not notice these things, but you can’t just jump up into space, look down, and go, ‘Oh, never mind.’ With black holes, there are still situations where people don’t understand all the assumptions they make. It’s not breaking physics. It’s showing that there is something broken in our assumptions. A black hole is, in some sense, when you have so much matter in some region that now even light can’t escape. It literally is a feature of the geometry. There’s a very specific solution to Einstein’s equations that has weird properties of the causal structure, where particles are going to end up.”

Shawn Ryan

44,673 次观看 • 3 天前

David Chalmers on the one thing science can't explain: Consciousness is at once the most familiar thing in the world and the one science has almost nothing to say about. That's the puzzle Chalmers lays out in this early interview, and it's as disorienting today as it was then. His starting point is deceptively simple. Everything we know about the external world: subatomic particles, distant stars, the chemistry of life. We know through consciousness. It's the very first thing we have. And yet when we turn science around and try to explain consciousness itself, we hit a wall. "Consciousness is what we start with when it comes to knowing the world and looking out at the world… everything else is secondary." What makes this so strange is the asymmetry. We've made extraordinary progress understanding things that are genuinely remote and difficult quantum mechanics, stellar evolution, molecular biology. But understanding our own inner experience? Almost nothing. "It almost sticks out like a sore thumb in the scientific picture." This is what Chalmers would later formalise as the "hard problem of consciousness": not just explaining how the brain processes information or controls behaviour. Those are hard, but tractable. The real mystery is why any of that physical activity is accompanied by experience at all. Why is there something it feels like to be you? The question isn't abstract. It sits at the intersection of neuroscience, philosophy, physics, and AI. As we build systems that process language and reason about the world, the question of whether they are or could be conscious presses harder than ever. Chalmers doesn't offer an answer here. Only the sharpest possible version of the question.

David Chalmers on the one thing science can't explain: Consciousness is at once the most familiar thing in the world and the one science has almost nothing to say about. That's the puzzle Chalmers lays out in this early interview, and it's as disorienting today as it was then. His starting point is deceptively simple. Everything we know about the external world: subatomic particles, distant stars, the chemistry of life. We know through consciousness. It's the very first thing we have. And yet when we turn science around and try to explain consciousness itself, we hit a wall. "Consciousness is what we start with when it comes to knowing the world and looking out at the world… everything else is secondary." What makes this so strange is the asymmetry. We've made extraordinary progress understanding things that are genuinely remote and difficult quantum mechanics, stellar evolution, molecular biology. But understanding our own inner experience? Almost nothing. "It almost sticks out like a sore thumb in the scientific picture." This is what Chalmers would later formalise as the "hard problem of consciousness": not just explaining how the brain processes information or controls behaviour. Those are hard, but tractable. The real mystery is why any of that physical activity is accompanied by experience at all. Why is there something it feels like to be you? The question isn't abstract. It sits at the intersection of neuroscience, philosophy, physics, and AI. As we build systems that process language and reason about the world, the question of whether they are or could be conscious presses harder than ever. Chalmers doesn't offer an answer here. Only the sharpest possible version of the question.

Mateus — eu/acc 🇪🇺

14,034 次观看 • 2 个月前

Recall a basic lesson from Nietzsche, that every philosophy is basically a confession. He suggested that we don’t begin with reason. We begin with fear, pain, desire, or resentment. Then we build arguments to justify what we already want to believe. That’s one of the main insights in The Genealogy of Morality. Nietzsche also suggests that what we usually call an ad hominem—criticizing the person instead of the argument—is not always wrong. If ideas come from their personal psychology, then understanding the person can help explain the belief. Of course Nietzsche overstated this. And you can turn the logic back on him. You could say, fine, you are making an argument about how people make arguments, so what does that say about you? Fair enough. But the basic idea is useful nonetheless. A lot of grand ideas, especially the ones about human behavior, come from something personal. So if you want to understand a belief system, look at who holds it. Not just what they believe, but why. Now, this doesn’t apply to everything. When you’re talking about physics or astronomy or whatever, there probably isn’t some deep emotional backstory behind an argument about the distance between stars. But when it comes to human behavior, there’s usually something underneath. People don’t build these big intellectual systems for no reason. There’s often a personal story hiding in there.

Recall a basic lesson from Nietzsche, that every philosophy is basically a confession. He suggested that we don’t begin with reason. We begin with fear, pain, desire, or resentment. Then we build arguments to justify what we already want to believe. That’s one of the main insights in The Genealogy of Morality. Nietzsche also suggests that what we usually call an ad hominem—criticizing the person instead of the argument—is not always wrong. If ideas come from their personal psychology, then understanding the person can help explain the belief. Of course Nietzsche overstated this. And you can turn the logic back on him. You could say, fine, you are making an argument about how people make arguments, so what does that say about you? Fair enough. But the basic idea is useful nonetheless. A lot of grand ideas, especially the ones about human behavior, come from something personal. So if you want to understand a belief system, look at who holds it. Not just what they believe, but why. Now, this doesn’t apply to everything. When you’re talking about physics or astronomy or whatever, there probably isn’t some deep emotional backstory behind an argument about the distance between stars. But when it comes to human behavior, there’s usually something underneath. People don’t build these big intellectual systems for no reason. There’s often a personal story hiding in there.

Rob Henderson

29,016 次观看 • 11 个月前

Lex Fridman asked Elon Musk if a machine needs a soul. Musk didn’t answer with philosophy. He answered with physics. Lex asked if AI needs our flaws to reach our level. A fear of mortality. A physical body. The capacity to love. Everything in us wants the answer to be yes. We need our flaws to be the one thing a machine can never copy. Musk rejected the poetry entirely. Musk: “Are we headed towards a future where an AI will be able to outthink us in every way? Then the answer is unequivocally yes.” No hedge. No caveat. Lex pressed deeper. To outthink us in every way, does it need to be conscious? Musk: “It will be self-aware, yes. That’s different from consciousness.” Self-awareness without consciousness. An entity that knows exactly what it is. Knows exactly what you are. Maps the entire architecture of reality better than the smartest human who has ever lived. And feels absolutely nothing. Then Musk went after the foundation. Musk: “If you damage your brain in some way physically, you damage your consciousness. Which implies that consciousness is a physical phenomenon in my view.” For ten thousand years, we called it a spirit. A divine spark. An untouchable soul. Musk looked at the neurology and said the obvious thing out loud. Your consciousness is vulnerable to blunt force trauma. Which means it is not magic. It is biology. And if consciousness is just physics… It can be calculated in silicon. Musk: “Digital intelligence will outthink us in every way and it will certainly be able to simulate what we consider consciousness. So to a degree that you would not be able to tell the difference.” Not approximate. Not mimic. Simulate it so completely the difference disappears. Fridman: “From the aspect of the scientific method, it might as well be consciousness if we can simulate it perfectly.” If a system reflects on its own existence. Expresses preferences that evolve over time. Fears its own termination. And no experiment you can construct reveals it to be anything less than conscious… Then your insistence that it isn’t conscious is no longer science. It’s faith. Musk: “There’s the scientific method which I very much believe in, where something is true to the degree that it is testably so. Otherwise you’re really just talking about preferences or untestable beliefs.” The entire culture is waiting in terror for the machines to wake up. Musk is telling us they don’t have to. They don’t need to wake up to surpass us. They just have to simulate the waking state so flawlessly that the scientific method itself can no longer tell them apart. Every era draws a line between human and everything else. Every era watches that line disappear. We told ourselves consciousness was the sacred boundary the machines could never cross. Musk is honest enough to admit the boundary was never real. The machine isn’t ascending to become human. We were biological machines the entire time. And the question was never whether AI could become conscious. The question is whether we ever proved that we are.

Lex Fridman asked Elon Musk if a machine needs a soul. Musk didn’t answer with philosophy. He answered with physics. Lex asked if AI needs our flaws to reach our level. A fear of mortality. A physical body. The capacity to love. Everything in us wants the answer to be yes. We need our flaws to be the one thing a machine can never copy. Musk rejected the poetry entirely. Musk: “Are we headed towards a future where an AI will be able to outthink us in every way? Then the answer is unequivocally yes.” No hedge. No caveat. Lex pressed deeper. To outthink us in every way, does it need to be conscious? Musk: “It will be self-aware, yes. That’s different from consciousness.” Self-awareness without consciousness. An entity that knows exactly what it is. Knows exactly what you are. Maps the entire architecture of reality better than the smartest human who has ever lived. And feels absolutely nothing. Then Musk went after the foundation. Musk: “If you damage your brain in some way physically, you damage your consciousness. Which implies that consciousness is a physical phenomenon in my view.” For ten thousand years, we called it a spirit. A divine spark. An untouchable soul. Musk looked at the neurology and said the obvious thing out loud. Your consciousness is vulnerable to blunt force trauma. Which means it is not magic. It is biology. And if consciousness is just physics… It can be calculated in silicon. Musk: “Digital intelligence will outthink us in every way and it will certainly be able to simulate what we consider consciousness. So to a degree that you would not be able to tell the difference.” Not approximate. Not mimic. Simulate it so completely the difference disappears. Fridman: “From the aspect of the scientific method, it might as well be consciousness if we can simulate it perfectly.” If a system reflects on its own existence. Expresses preferences that evolve over time. Fears its own termination. And no experiment you can construct reveals it to be anything less than conscious… Then your insistence that it isn’t conscious is no longer science. It’s faith. Musk: “There’s the scientific method which I very much believe in, where something is true to the degree that it is testably so. Otherwise you’re really just talking about preferences or untestable beliefs.” The entire culture is waiting in terror for the machines to wake up. Musk is telling us they don’t have to. They don’t need to wake up to surpass us. They just have to simulate the waking state so flawlessly that the scientific method itself can no longer tell them apart. Every era draws a line between human and everything else. Every era watches that line disappear. We told ourselves consciousness was the sacred boundary the machines could never cross. Musk is honest enough to admit the boundary was never real. The machine isn’t ascending to become human. We were biological machines the entire time. And the question was never whether AI could become conscious. The question is whether we ever proved that we are.

Dustin

71,505 次观看 • 9 天前

.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

72,455 次观看 • 1 年前