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Google DeepMind CEO Demis Hassabis believes there is virtually no limit to what AI can eventually achieve. "humans as biological information processing systems". He is working on the premise that the entire universe is "computable," meaning that anything that exists can technically be modeled by a machine. He says...

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Rohan Paul

153,370 subscribers

84,528 次观看 • 8 个月前 •via X (Twitter)

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Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)
0:53

Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)

Rohan Paul

334,691 次观看 • 11 个月前

📁 Demis Hassabis, CEO of DeepMind, says that current AI systems are not self-aware or conscious in any real sense. He explains that self-awareness is not an explicit goal, but it could emerge implicitly as models develop a deeper understanding of self and others. He warns that if a machine did become self-aware, we might not even be able to recognize it.
0:30

📁 Demis Hassabis, CEO of DeepMind, says that current AI systems are not self-aware or conscious in any real sense. He explains that self-awareness is not an explicit goal, but it could emerge implicitly as models develop a deeper understanding of self and others. He warns that if a machine did become self-aware, we might not even be able to recognize it.

Jon Hernandez

78,350 次观看 • 8 个月前

Demis Hassabis says DeepMind is on track to solve intelligence by around 2030 As AI enters the "agentic era" of autonomy this year, the risk is that bad actors could repurpose the tech for harm "then we have to make sure... that these systems do what we expect them to do"
1:39

Demis Hassabis says DeepMind is on track to solve intelligence by around 2030 As AI enters the "agentic era" of autonomy this year, the risk is that bad actors could repurpose the tech for harm "then we have to make sure... that these systems do what we expect them to do"

Haider.

21,471 次观看 • 5 个月前

.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.
1:37

.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

33,110 次观看 • 1 年前

Demis Hassabis, CEO of Google DeepMind and Nobel laureate, says the AGI definition the industry uses is too low a bar. His Einstein test: train a system on a 1901 knowledge cutoff and ask it to invent special relativity. "The human brain is the only existence proof we have that general intelligence is even possible." "That's a pretty high bar, and it means that it's probably higher bar than just being able to do some useful economic work." "The type of test I would have is like an Einstein test of, you know, let's train one of these systems with a 1901 knowledge cutoff. Can it invent special relativity like Einstein did in 1905?" "What you'd actually want is something a future version of AlphaGo to be able to invent Go, right? Invent a game as deep and as complex and elegant and as beautiful as Go, not just come up with a strategy within the game." "I don't think today's systems are yet capable of doing that, but I think they will be able to in the future." - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, on The Next Big Thing.
2:52

Demis Hassabis, CEO of Google DeepMind and Nobel laureate, says the AGI definition the industry uses is too low a bar. His Einstein test: train a system on a 1901 knowledge cutoff and ask it to invent special relativity. "The human brain is the only existence proof we have that general intelligence is even possible." "That's a pretty high bar, and it means that it's probably higher bar than just being able to do some useful economic work." "The type of test I would have is like an Einstein test of, you know, let's train one of these systems with a 1901 knowledge cutoff. Can it invent special relativity like Einstein did in 1905?" "What you'd actually want is something a future version of AlphaGo to be able to invent Go, right? Invent a game as deep and as complex and elegant and as beautiful as Go, not just come up with a strategy within the game." "I don't think today's systems are yet capable of doing that, but I think they will be able to in the future." - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, on The Next Big Thing.

Karl Mehta

72,911 次观看 • 22 天前

In 2025, DeepMind CEO Demis Hassabis gave a 60-minute Cambridge lecture on AI as a discovery engine. This is bigger than chatbots. He explained: - The "Move 37" method - A billion years of PhD time - Biology as an information system 12 lessons that will blow your mind: 🧵
1:00:10

In 2025, DeepMind CEO Demis Hassabis gave a 60-minute Cambridge lecture on AI as a discovery engine. This is bigger than chatbots. He explained: - The "Move 37" method - A billion years of PhD time - Biology as an information system 12 lessons that will blow your mind: 🧵

andrew engler

109,243 次观看 • 3 个月前

Demis Hassabis just said something that should unsettle every scientist alive. Hassabis: “I do think that, ultimately, underlying physics is information theory. So I do think we’re in a computational universe.” The CEO of Google DeepMind is telling you reality runs on code. Not metaphorically. Structurally. AlphaFold didn’t approximate protein structures. It solved them. Not because DeepMind built a better guesser. Because proteins were never physical objects. They were always data. Hassabis: “The fact that these systems are able to model real structures in nature is quite interesting and telling.” He said telling. Not impressive. Not promising. Telling. As in the results reveal something about what reality actually is. AlphaGo found patterns in a 3,000-year-old game no civilization ever noticed. AlphaFold decoded biology in hours that took researchers decades. These systems aren’t approximating nature. They’re reading it fluently. Because nature was always written in a language machines understand better than we do. Hassabis: “Maybe at some point I’ll write up a scientific paper about what I think that really means in terms of what’s actually going on here in reality.” The man running the most advanced AI lab on Earth thinks he’s found something fundamental about existence itself. And he’s not ready to say it yet. Every era thinks it knows what the universe is made of. Atoms. Waves. Strings. Hassabis is suggesting the answer was never matter. It was always math. And the machine he built to fold proteins might have accidentally proved it. The question that should keep you up tonight isn’t whether AI can simulate reality. It’s whether reality was the simulation first.
1:11

Demis Hassabis just said something that should unsettle every scientist alive. Hassabis: “I do think that, ultimately, underlying physics is information theory. So I do think we’re in a computational universe.” The CEO of Google DeepMind is telling you reality runs on code. Not metaphorically. Structurally. AlphaFold didn’t approximate protein structures. It solved them. Not because DeepMind built a better guesser. Because proteins were never physical objects. They were always data. Hassabis: “The fact that these systems are able to model real structures in nature is quite interesting and telling.” He said telling. Not impressive. Not promising. Telling. As in the results reveal something about what reality actually is. AlphaGo found patterns in a 3,000-year-old game no civilization ever noticed. AlphaFold decoded biology in hours that took researchers decades. These systems aren’t approximating nature. They’re reading it fluently. Because nature was always written in a language machines understand better than we do. Hassabis: “Maybe at some point I’ll write up a scientific paper about what I think that really means in terms of what’s actually going on here in reality.” The man running the most advanced AI lab on Earth thinks he’s found something fundamental about existence itself. And he’s not ready to say it yet. Every era thinks it knows what the universe is made of. Atoms. Waves. Strings. Hassabis is suggesting the answer was never matter. It was always math. And the machine he built to fold proteins might have accidentally proved it. The question that should keep you up tonight isn’t whether AI can simulate reality. It’s whether reality was the simulation first.

Dustin

112,048 次观看 • 2 个月前

Ilya Sutskever predicts that in the coming years—whether it’s three, five, or ten—AI will be able to do everything humans can do. He argues that since the brain is a biological computer, a digital computer should, in theory, be capable of learning and performing all the same tasks. This belief underpins his confidence in the arrival of truly general AI.
2:01

Ilya Sutskever predicts that in the coming years—whether it’s three, five, or ten—AI will be able to do everything humans can do. He argues that since the brain is a biological computer, a digital computer should, in theory, be capable of learning and performing all the same tasks. This belief underpins his confidence in the arrival of truly general AI.

Wes Roth

14,017 次观看 • 1 年前

We are no longer building software. We are building agents. Systems that don’t wait for a prompt. Systems that don’t ask for permission. Systems that simply execute. DeepMind CEO Demis Hassabis just revealed the terrifying duality of the agentic era. Hassabis: “Better healthcare, better drugs, helping with climate change and energy. All of these things are actually on the cusp of happening.” Post-scarcity abundance isn’t fantasy. It is a scheduled update. But macro-architects do not engineer for the best-case scenario. They engineer for the failure state. Hassabis identified the two exact vectors that could collapse the transition to superintelligence. The first is human malice. Hassabis: “Bad actors repurposing these technologies for harmful ends.” Intelligence is the ultimate dual-use weapon. If a neural network can invent a compound to cure a disease, it can engineer a pathogen to start a pandemic. The machine has no morality. It only has parameters. The second vector is architectural. Hassabis: “As these AI systems get more powerful, more autonomous, maybe entering the agentic era… how do we make sure we can build robust enough guardrails to keep them doing what we want?” Read that again. The people building the superintelligence do not know how to steer it once it wakes up. For the entire history of computing, the machine waited. An agentic system does not wait. It acts. We are handing the steering wheel to an entity operating at the speed of light, while our brains process information at the speed of chemistry. Once it begins executing, our biological reaction time is physically too slow to pull the plug. The question of control stops being a philosophical debate. It becomes a mathematical impossibility. Because by the time human biology realizes it needs to ask the question… The answer is already no.
0:32

We are no longer building software. We are building agents. Systems that don’t wait for a prompt. Systems that don’t ask for permission. Systems that simply execute. DeepMind CEO Demis Hassabis just revealed the terrifying duality of the agentic era. Hassabis: “Better healthcare, better drugs, helping with climate change and energy. All of these things are actually on the cusp of happening.” Post-scarcity abundance isn’t fantasy. It is a scheduled update. But macro-architects do not engineer for the best-case scenario. They engineer for the failure state. Hassabis identified the two exact vectors that could collapse the transition to superintelligence. The first is human malice. Hassabis: “Bad actors repurposing these technologies for harmful ends.” Intelligence is the ultimate dual-use weapon. If a neural network can invent a compound to cure a disease, it can engineer a pathogen to start a pandemic. The machine has no morality. It only has parameters. The second vector is architectural. Hassabis: “As these AI systems get more powerful, more autonomous, maybe entering the agentic era… how do we make sure we can build robust enough guardrails to keep them doing what we want?” Read that again. The people building the superintelligence do not know how to steer it once it wakes up. For the entire history of computing, the machine waited. An agentic system does not wait. It acts. We are handing the steering wheel to an entity operating at the speed of light, while our brains process information at the speed of chemistry. Once it begins executing, our biological reaction time is physically too slow to pull the plug. The question of control stops being a philosophical debate. It becomes a mathematical impossibility. Because by the time human biology realizes it needs to ask the question… The answer is already no.

Dustin

10,956 次观看 • 5 个月前

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 次观看 • 2 个月前

According to Bentov, consciousness evolves to the 'absolute' which is the source of all consciousness. Matter, composed of quanta of energy, is the vibrating, changing component of pure consciousness. The absolute is fixed, manifest and invisible. Bentov proposed that the brain acts as a transducer, converting the energy of consciousness into the electrical and chemical signals that are used to communicate information within the body. He also believed that the brain has the ability to tune into different frequencies of consciousness, allowing individuals to experience different states of awareness. Bentov's theory is based on the idea that consciousness is a fundamental aspect of the universe and is not limited to the brain or the body. He argued that consciousness is non-local, meaning it is not bound by space and time and can exist independently of the physical body. Bentov's theory has been influential in the field of consciousness studies, but it remains a subject of debate and is not widely accepted by mainstream science.
2:39

According to Bentov, consciousness evolves to the 'absolute' which is the source of all consciousness. Matter, composed of quanta of energy, is the vibrating, changing component of pure consciousness. The absolute is fixed, manifest and invisible. Bentov proposed that the brain acts as a transducer, converting the energy of consciousness into the electrical and chemical signals that are used to communicate information within the body. He also believed that the brain has the ability to tune into different frequencies of consciousness, allowing individuals to experience different states of awareness. Bentov's theory is based on the idea that consciousness is a fundamental aspect of the universe and is not limited to the brain or the body. He argued that consciousness is non-local, meaning it is not bound by space and time and can exist independently of the physical body. Bentov's theory has been influential in the field of consciousness studies, but it remains a subject of debate and is not widely accepted by mainstream science.

Vicky Verma

390,608 次观看 • 2 年前

Never forget that Donald Trump was the only person who helped the Epstein victims with useful information back when Epstein had the entire system blackmailed & controlled. He also kicked Epstein out of Mar-a-Lago. Now, as President, he's releasing the truth to the public. "The only thing that I can say about President Trump is that he is the only person who, in 2009, when I served a lot of subpoenas on a lot of people... He is the only person who picked up the phone and said, 'Let's just talk. I'll give you as much time as you want. I'll tell you what you need to know.' And was very helpful in the information that he gave and gave no indication whatsoever that he was involved in anything untoward whatsoever, but had good information that checked out and that helped us and that we didn't have to take a deposition of him." - Epstein Victim Attorney Bradley Edwards. God works in mysterious ways.
1:06

Never forget that Donald Trump was the only person who helped the Epstein victims with useful information back when Epstein had the entire system blackmailed & controlled. He also kicked Epstein out of Mar-a-Lago. Now, as President, he's releasing the truth to the public. "The only thing that I can say about President Trump is that he is the only person who, in 2009, when I served a lot of subpoenas on a lot of people... He is the only person who picked up the phone and said, 'Let's just talk. I'll give you as much time as you want. I'll tell you what you need to know.' And was very helpful in the information that he gave and gave no indication whatsoever that he was involved in anything untoward whatsoever, but had good information that checked out and that helped us and that we didn't have to take a deposition of him." - Epstein Victim Attorney Bradley Edwards. God works in mysterious ways.

George

1,358,718 次观看 • 1 年前

David Icke in 2024: “They know that the body is a biological computer. It can be manipulated, as computers can be manipulated, to process information in a different way.” “One of the great manipulative techniques is to sell the idea of inevitability.” “We have this global cult, a global network of secret societies that is driving the direction of the human society, way beyond presidents.” “This reality is actually a simulation. It's a incredibly advanced version of virtual reality game.”
1:03

David Icke in 2024: “They know that the body is a biological computer. It can be manipulated, as computers can be manipulated, to process information in a different way.” “One of the great manipulative techniques is to sell the idea of inevitability.” “We have this global cult, a global network of secret societies that is driving the direction of the human society, way beyond presidents.” “This reality is actually a simulation. It's a incredibly advanced version of virtual reality game.”

Shadow Intel

67,962 次观看 • 1 个月前

David Icke in 2024: “They know that the body is a biological computer. It can be manipulated, as computers can be manipulated, to process information in a different way.” “One of the great manipulative techniques is to sell the idea of inevitability.” “We have this global cult, a global network of secret societies that is driving the direction of the human society, way beyond presidents.” “This reality is actually a simulation. It's a incredibly advanced version of virtual reality game.”
0:58

David Icke in 2024: “They know that the body is a biological computer. It can be manipulated, as computers can be manipulated, to process information in a different way.” “One of the great manipulative techniques is to sell the idea of inevitability.” “We have this global cult, a global network of secret societies that is driving the direction of the human society, way beyond presidents.” “This reality is actually a simulation. It's a incredibly advanced version of virtual reality game.”

Defiant Ghost

113,030 次观看 • 4 个月前

Corporations that are purely AI and robotics will vastly outperform any corporations that have people in the loop You can think of it like how 'computer' used to be a job that humans had. You would go and get a job as a computer where you would do calculations. They had entire skyscrapers full of humans....20, 30 floors of humans...just doing calculations. Now, that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet. That spreadsheet can do vastly more calculations than an entire building full of human computers So, you think about it: what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all of the cells in your spreadsheet were calculated by the computer. And so, really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop. It will happen very quickly
1:22

Corporations that are purely AI and robotics will vastly outperform any corporations that have people in the loop You can think of it like how 'computer' used to be a job that humans had. You would go and get a job as a computer where you would do calculations. They had entire skyscrapers full of humans....20, 30 floors of humans...just doing calculations. Now, that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet. That spreadsheet can do vastly more calculations than an entire building full of human computers So, you think about it: what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all of the cells in your spreadsheet were calculated by the computer. And so, really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop. It will happen very quickly

X Freeze

16,843,827 次观看 • 6 个月前

Demis Hassabis, Nobel laureate and CEO of Google DeepMind: "I think one day, maybe we can cure all disease with the help of AI. Within the next decade. I don't see why not." This is not a hype account. It is the man whose AI mapped 200 million protein structures in a single year, work that used to take a lifetime. A new drug normally takes ten years and billions of dollars. He thinks AI cuts that to months, maybe weeks. Musk said your future doctor will be AI. Hassabis is saying the disease itself might not be waiting for you by then. We treated illness as the fixed price of being alive. Two Nobel-level labs are now quietly saying that price was a choice.
4:57

Demis Hassabis, Nobel laureate and CEO of Google DeepMind: "I think one day, maybe we can cure all disease with the help of AI. Within the next decade. I don't see why not." This is not a hype account. It is the man whose AI mapped 200 million protein structures in a single year, work that used to take a lifetime. A new drug normally takes ten years and billions of dollars. He thinks AI cuts that to months, maybe weeks. Musk said your future doctor will be AI. Hassabis is saying the disease itself might not be waiting for you by then. We treated illness as the fixed price of being alive. Two Nobel-level labs are now quietly saying that price was a choice.

Casper

25,867 次观看 • 18 天前

“Scientific progress is becoming computable.” DeepMind CEO Demis Hassabis says AI is becoming a scientific infrastructure layer, not just a productivity tool. At Google I/O, he introduced Gemini for Science: a new set of AI systems designed to help researchers read papers, write code, and generate hypotheses faster. The real shift is that research itself is starting to scale like software.
0:53

“Scientific progress is becoming computable.” DeepMind CEO Demis Hassabis says AI is becoming a scientific infrastructure layer, not just a productivity tool. At Google I/O, he introduced Gemini for Science: a new set of AI systems designed to help researchers read papers, write code, and generate hypotheses faster. The real shift is that research itself is starting to scale like software.

Jon Hernandez

25,478 次观看 • 2 个月前