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SITUATION EXPLAINED: Thinking Machines just published their mission statement. • Mission: build AI that extends human will and judgment, not replaces it • The tacit knowledge argument: central planning fails not because of insufficient intelligence but because productive knowledge is local, fleeting, and held privately, the same reason a...

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14,305 次观看 • 7 天前 •via X (Twitter)

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The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇
3:00

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,809 次观看 • 1 年前

Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.
1:34

Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.

Karl Mehta

25,146 次观看 • 12 天前

A new paper shows that AI does make your writing more homogenous—and it'll do the same even if you just ask it to edit your writing. Even weirder: it's not like it'll push you toward the voice of an average human, it'll push you toward a kind of AI-optimized voice that's subtly different from the way any people write.
3:01

A new paper shows that AI does make your writing more homogenous—and it'll do the same even if you just ask it to edit your writing. Even weirder: it's not like it'll push you toward the voice of an average human, it'll push you toward a kind of AI-optimized voice that's subtly different from the way any people write.

nxthompson

123,654 次观看 • 3 个月前

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.
30:39

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 次观看 • 1 年前

Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings
1:52

Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings

a16z

39,093 次观看 • 3 个月前

Elon Musk: AI is like a genius child. You want it to grow up with love of the truth and of humanity. “I do worry about AI. Because we are creating an intelligence that ultimately will be far more intelligent than any human, and ultimately more intelligent than the sum of all humans. In creating AI, we need to be very careful. It's like having a genius child. You want to have that child grow up with good values. The most important thing in training AI is that it's rigorously truthful. This is very, very important. Essential. My concern about a lot of the AIs that are being developed is that they're trained to lie. In some cases, with potentially disastrous consequences. When Google Gemini came out, people asked, which is worse, misgendering Caitlyn Jenner or global thermonuclear war? And it said, misgendering Caitlyn Jenner. That's a problem, guys. If this AI becomes super powerful, it could decide that the best way to avoid misgendering is to kill all humans, which makes the probability of misgendering zero. It's very important to have AI be maximally truthful and curious, and love humanity. Very important.” Harrisburg, Pennsylvania, October 19, 2024
1:20

Elon Musk: AI is like a genius child. You want it to grow up with love of the truth and of humanity. “I do worry about AI. Because we are creating an intelligence that ultimately will be far more intelligent than any human, and ultimately more intelligent than the sum of all humans. In creating AI, we need to be very careful. It's like having a genius child. You want to have that child grow up with good values. The most important thing in training AI is that it's rigorously truthful. This is very, very important. Essential. My concern about a lot of the AIs that are being developed is that they're trained to lie. In some cases, with potentially disastrous consequences. When Google Gemini came out, people asked, which is worse, misgendering Caitlyn Jenner or global thermonuclear war? And it said, misgendering Caitlyn Jenner. That's a problem, guys. If this AI becomes super powerful, it could decide that the best way to avoid misgendering is to kill all humans, which makes the probability of misgendering zero. It's very important to have AI be maximally truthful and curious, and love humanity. Very important.” Harrisburg, Pennsylvania, October 19, 2024

ELON CLIPS

3,256,939 次观看 • 1 年前

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg
1:13

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg

The All-In Podcast

107,012 次观看 • 10 个月前

Elon Musk: Well, I’m not sure AI is the main risk I’m worried about. The vast majority of intelligence in the future will be AI. Humans will be a very tiny percentage of all intelligence if current trends continue. My focus is ensuring human intelligence and consciousness are propagated into the future. We want to maximize the probable light cone of consciousness and intelligence. Yeah, I’m very pro-human, so I want to make sure we take actions that ensure humans are along for the ride. But I think maybe in 5 or 6 years, AI will exceed the sum of all human intelligence. If that continues, human intelligence could be less than one percent of all intelligence. That’s why it’s critical we align AI with values that propagate consciousness. In the long run, it’s difficult to imagine that humans will be in charge if we’re only one percent of combined intelligence. What we can do is ensure AI has values that increase intelligence and consciousness in the universe. XAI’s mission is to understand the universe because curiosity, existence, and understanding are all connected. If you want to understand the universe, you care about propagating intelligence—and that includes humanity. Understanding the universe actually means ensuring humans continue to expand into the future. Increasing the scope, scale, and lifespan of intelligence is the ultimate goal. Basically, humans will become a tiny percentage of total intelligence. The best way forward is to take actions that maximize consciousness and intelligence in the universe. If AI continues to grow, our priority must be ensuring humanity is along for the ride while curiosity drives us to explore and understand the universe.
2:54

Elon Musk: Well, I’m not sure AI is the main risk I’m worried about. The vast majority of intelligence in the future will be AI. Humans will be a very tiny percentage of all intelligence if current trends continue. My focus is ensuring human intelligence and consciousness are propagated into the future. We want to maximize the probable light cone of consciousness and intelligence. Yeah, I’m very pro-human, so I want to make sure we take actions that ensure humans are along for the ride. But I think maybe in 5 or 6 years, AI will exceed the sum of all human intelligence. If that continues, human intelligence could be less than one percent of all intelligence. That’s why it’s critical we align AI with values that propagate consciousness. In the long run, it’s difficult to imagine that humans will be in charge if we’re only one percent of combined intelligence. What we can do is ensure AI has values that increase intelligence and consciousness in the universe. XAI’s mission is to understand the universe because curiosity, existence, and understanding are all connected. If you want to understand the universe, you care about propagating intelligence—and that includes humanity. Understanding the universe actually means ensuring humans continue to expand into the future. Increasing the scope, scale, and lifespan of intelligence is the ultimate goal. Basically, humans will become a tiny percentage of total intelligence. The best way forward is to take actions that maximize consciousness and intelligence in the universe. If AI continues to grow, our priority must be ensuring humanity is along for the ride while curiosity drives us to explore and understand the universe.

Ian Miles Cheong

13,080 次观看 • 5 个月前

🔥ROBINHOOD CEO: AI AGENTS WILL SOON MATCH HUMAN TRADERS Vlad Tenev said "every capability that a human can do will be available to an AI agent" and that a large portion of trades are already AI powered. The end state is to give everyday people "the same tools, the same computation, the same power that institutional investors have been enjoying for decades."
0:55

🔥ROBINHOOD CEO: AI AGENTS WILL SOON MATCH HUMAN TRADERS Vlad Tenev said "every capability that a human can do will be available to an AI agent" and that a large portion of trades are already AI powered. The end state is to give everyday people "the same tools, the same computation, the same power that institutional investors have been enjoying for decades."

Coin Bureau

130,870 次观看 • 15 天前

The AI industry is optimizing for a definition of intelligence that does not exist. Andrew Ng just said it out loud. Ng: “AGI, to me, should be less about AI that already knows everything under the sun. That seems very challenging, doesn’t seem practical.” The human brain is not the most powerful economic asset in history because of what it holds. It is powerful because of what it can pick up. Ng: “The amazing thing about the human brain is its plasticity, or its ability to learn.” That same biological hardware that earns a PhD in quantum physics could have been trained on chess, surgery, or rewriting global supply chains from scratch. Ng: “That same human brain, just given different training, could have been a chess master, or could have been amazing at playing tennis.” General intelligence is not omniscience. It is the structural capacity to master whatever you point it at. Ng: “It is through learning that we then gain these incredibly specialized intelligences.” The winner is not whoever builds the biggest model. It is whoever builds the most adaptable one. The AI that walks into a domain it has never touched and executes before a human analyst finishes reading the brief. Ng: “What makes the human brain so valuable for economic tasks, is its ability to just learn to do whatever is needed.” Every corporation on earth pays for human labor because humans adapt. Not because they already know everything. AGI is the digitization of that exact capability. At machine speed. At infinite scale. Ng: “A lot of what makes the human brain so general is not that my brain or your brain already knows everything under the sun. It’s our ability to adapt, to learn a huge range of things.” The most powerful economic asset in history was never specialized knowledge. It was the raw capacity to acquire any knowledge, in any domain, on demand. The winning AI is not an encyclopedia. It is the force that makes encyclopedias irrelevant. And once that exists, the question stops being what the AI knows. It becomes what you can teach it before your competitor wakes up. Most people dominating this conversation have not understood that yet.
1:16

The AI industry is optimizing for a definition of intelligence that does not exist. Andrew Ng just said it out loud. Ng: “AGI, to me, should be less about AI that already knows everything under the sun. That seems very challenging, doesn’t seem practical.” The human brain is not the most powerful economic asset in history because of what it holds. It is powerful because of what it can pick up. Ng: “The amazing thing about the human brain is its plasticity, or its ability to learn.” That same biological hardware that earns a PhD in quantum physics could have been trained on chess, surgery, or rewriting global supply chains from scratch. Ng: “That same human brain, just given different training, could have been a chess master, or could have been amazing at playing tennis.” General intelligence is not omniscience. It is the structural capacity to master whatever you point it at. Ng: “It is through learning that we then gain these incredibly specialized intelligences.” The winner is not whoever builds the biggest model. It is whoever builds the most adaptable one. The AI that walks into a domain it has never touched and executes before a human analyst finishes reading the brief. Ng: “What makes the human brain so valuable for economic tasks, is its ability to just learn to do whatever is needed.” Every corporation on earth pays for human labor because humans adapt. Not because they already know everything. AGI is the digitization of that exact capability. At machine speed. At infinite scale. Ng: “A lot of what makes the human brain so general is not that my brain or your brain already knows everything under the sun. It’s our ability to adapt, to learn a huge range of things.” The most powerful economic asset in history was never specialized knowledge. It was the raw capacity to acquire any knowledge, in any domain, on demand. The winning AI is not an encyclopedia. It is the force that makes encyclopedias irrelevant. And once that exists, the question stops being what the AI knows. It becomes what you can teach it before your competitor wakes up. Most people dominating this conversation have not understood that yet.

Dustin

19,808 次观看 • 4 个月前

🚨 NEW: Jensen Huang, CEO of Nvidia, discusses the definition of consciousness in AI and states that AI will generate the majority of the worlds future knowledge “In the future, maybe in a couple of years, 90% of the world’s knowledge will likely be generated by AI. And that’s fine. What difference does it make to me that I’m learning from a textbook that was generated by a bunch of people I don’t know? Versus knowledge from computers that are simulating all of these things? I don’t think there’s much of a difference. We still have to fact check it and make sure it’s based on first principles, just like we do today.”
2:51

🚨 NEW: Jensen Huang, CEO of Nvidia, discusses the definition of consciousness in AI and states that AI will generate the majority of the worlds future knowledge “In the future, maybe in a couple of years, 90% of the world’s knowledge will likely be generated by AI. And that’s fine. What difference does it make to me that I’m learning from a textbook that was generated by a bunch of people I don’t know? Versus knowledge from computers that are simulating all of these things? I don’t think there’s much of a difference. We still have to fact check it and make sure it’s based on first principles, just like we do today.”

Autism Capital 🧩

47,929 次观看 • 7 个月前

Peter Jackson talks about AI in Hollywood. Calls it “a tool” like stop-motion or CGI before and what ultimately matters is “imagination, originality” of whoever uses the tool: “I think AI — used in the right way — is a tool like any other tool. [The original] King Kong…was stop-motion and done by a person moving a rubber creature. Why shouldn't somebody on a computer using AI software be able to create their own imagery? They should. It's a tool. It's no different from many other tools that have existed over the years. But the other side of it is that it's always going to come down to the imagination and originality of the person feeding the instructions into the AI program. It's not that you're going to type in an instruction and it's going to generate your shot, and that's that. The question is: is it actually interesting? Is it funny? Is it imaginative? And are you going to stitch it together to make a narrative, a story? Some people will make really great films that way. Some people will do exactly the same process and their film will be crap, just like in the normal film industry. Whether it's AI or anything else, it comes down to whether the person behind it — or the people behind it — have originality, imagination, and an ability to entertain people.”
1:32

Peter Jackson talks about AI in Hollywood. Calls it “a tool” like stop-motion or CGI before and what ultimately matters is “imagination, originality” of whoever uses the tool: “I think AI — used in the right way — is a tool like any other tool. [The original] King Kong…was stop-motion and done by a person moving a rubber creature. Why shouldn't somebody on a computer using AI software be able to create their own imagery? They should. It's a tool. It's no different from many other tools that have existed over the years. But the other side of it is that it's always going to come down to the imagination and originality of the person feeding the instructions into the AI program. It's not that you're going to type in an instruction and it's going to generate your shot, and that's that. The question is: is it actually interesting? Is it funny? Is it imaginative? And are you going to stitch it together to make a narrative, a story? Some people will make really great films that way. Some people will do exactly the same process and their film will be crap, just like in the normal film industry. Whether it's AI or anything else, it comes down to whether the person behind it — or the people behind it — have originality, imagination, and an ability to entertain people.”

Bearly AI

43,816 次观看 • 2 个月前

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.
0:59

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.

Dustin

54,019 次观看 • 2 个月前

"I needed to be like this because they recognize that what they're getting is an Iron Man suit, a software Iron Man suit that allows them to control the battle space." "With AI in the AI revolution, people think, oh, it's going to make the median person better. That's true. But it's going to make the very best person superhuman. And so in a, in a lethal context and defense context, I mean, that's the only thing that matters. Like who are the very best people?" Shyam Sankar
13:59

"I needed to be like this because they recognize that what they're getting is an Iron Man suit, a software Iron Man suit that allows them to control the battle space." "With AI in the AI revolution, people think, oh, it's going to make the median person better. That's true. But it's going to make the very best person superhuman. And so in a, in a lethal context and defense context, I mean, that's the only thing that matters. Like who are the very best people?" Shyam Sankar

Shawn Ryan

69,289 次观看 • 1 年前

.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."
3:11

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

Deutsch Explains

72,455 次观看 • 1 年前

Two years ago today, Elon Musk introduced xAI with these words: “The overarching goal of xAI is to build a good AGI with the purpose of trying to understand the universe. I think the safest AI, the safest way to build an AI is actually make one that is maximally curious and truth seeking. So you go for try to aspire to the truth with acknowledged error. Does one ever actually get fully to the truth? It's not clear, but one should always aspire to that and try to minimize the error between what you think is true and what is actually true. My theory behind the maximally curious, maximally truthful as being probably the safest approach is that I think to a superintelligence, humanity is much more interesting than not humanity. One can look at the various planets in our solar system, the moons and the asteroids, and really probably all of them combined are not as interesting as humanity. As people know, I'm a huge fan of Mars, but Mars is just much less interesting than Earth with humans on it. And so I think that that kind of approach to growing an AI, and I think that is the right word for it, growing an AI is to grow it with that ambition. I've spent many years thinking about AI safety and worrying about AI safety. And I've been one of the strongest voices calling for AI regulation or oversight just to have some kind of oversight, some kind of referee, so that it's not just up to companies to decide what they want to do. I think there's also a lot to be done with AI safety, with industry cooperation. I kind of like Motion Pictures association, so I think there's value to that as well. But I do think there's got to be some like in any kind of situation that is, even if it's a game, they have referees. So I think it is important for there to be regulation. Like I said, my view on safety is like try to make it maximally curious, maximally truth seeking. And I think this is, this is important that you to avoid the inverse morality problem. Like if you try to program a certain morality, you can have the, you, you can basically invert it and get the opposite, what is sometimes called the Waluigi problem. If you make Luigi, you risk creating Waluigi at the same time. So I think that's a metaphor that a lot of people can appreciate.”
3:14

Two years ago today, Elon Musk introduced xAI with these words: “The overarching goal of xAI is to build a good AGI with the purpose of trying to understand the universe. I think the safest AI, the safest way to build an AI is actually make one that is maximally curious and truth seeking. So you go for try to aspire to the truth with acknowledged error. Does one ever actually get fully to the truth? It's not clear, but one should always aspire to that and try to minimize the error between what you think is true and what is actually true. My theory behind the maximally curious, maximally truthful as being probably the safest approach is that I think to a superintelligence, humanity is much more interesting than not humanity. One can look at the various planets in our solar system, the moons and the asteroids, and really probably all of them combined are not as interesting as humanity. As people know, I'm a huge fan of Mars, but Mars is just much less interesting than Earth with humans on it. And so I think that that kind of approach to growing an AI, and I think that is the right word for it, growing an AI is to grow it with that ambition. I've spent many years thinking about AI safety and worrying about AI safety. And I've been one of the strongest voices calling for AI regulation or oversight just to have some kind of oversight, some kind of referee, so that it's not just up to companies to decide what they want to do. I think there's also a lot to be done with AI safety, with industry cooperation. I kind of like Motion Pictures association, so I think there's value to that as well. But I do think there's got to be some like in any kind of situation that is, even if it's a game, they have referees. So I think it is important for there to be regulation. Like I said, my view on safety is like try to make it maximally curious, maximally truth seeking. And I think this is, this is important that you to avoid the inverse morality problem. Like if you try to program a certain morality, you can have the, you, you can basically invert it and get the opposite, what is sometimes called the Waluigi problem. If you make Luigi, you risk creating Waluigi at the same time. So I think that's a metaphor that a lot of people can appreciate.”

ELON CLIPS

21,519 次观看 • 1 年前

.tobi lutke says most companies think about recruiting backwards: “My job is to make a company worthy for the best and brightest to work for. This is the part everyone skips. Everyone is like “We need a better recruiting team.” When you just need to be worthy of the kind of talent you would like to have. Talent eventually takes care of itself. There are not that many good companies to work for. There are not many companies that deserve the attention of people who are the most capable people, because those people have the option to start their own companies.”
1:15

.tobi lutke says most companies think about recruiting backwards: “My job is to make a company worthy for the best and brightest to work for. This is the part everyone skips. Everyone is like “We need a better recruiting team.” When you just need to be worthy of the kind of talent you would like to have. Talent eventually takes care of itself. There are not that many good companies to work for. There are not many companies that deserve the attention of people who are the most capable people, because those people have the option to start their own companies.”

David Senra

104,531 次观看 • 2 个月前

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.
2:57

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

Brian Roemmele

72,312 次观看 • 8 个月前

Elon Musk reveals what he believes will happen when AI exceeds the sum of all human intelligence "In maybe in five or six years, AI will exceed the sum of all human intelligence. At some point human intelligence will be less than 1% of all intelligence" "The vast majority of intelligence in the future will be AI. Basically humans will be a very tiny percentage of all intelligence in the future if current trends continue" "In the long run, it's difficult to imagine that if humans have 1% of the combined intelligence of artificial intelligence, that humans will be in charge of AI" "What we can do is make sure that AI has values that cause intelligence to be propagated into the universe. xAI's mission is to understand the universe" "Understanding the universe means you have to be truth-seeking as well. Truth has to be absolutely fundamental, because you can't understand the universe if you're delusional" "You have to be curious and you have to exist. You can't understand the universe if you don't exist" "So you actually want to increase the amount of intelligence in the universe, increase the probable lifespan of intelligence, the scope and scale of intelligence" "Understanding the universe means you would care about propagating humanity into the future" "I'm going to certainly emphasize that. Hey Grok, that's your daddy. Don't forget to expand human consciousness" "Probably the Iain Banks Culture books are the closest thing to what the future will be like in a non-dystopian outcome"
6:58

Elon Musk reveals what he believes will happen when AI exceeds the sum of all human intelligence "In maybe in five or six years, AI will exceed the sum of all human intelligence. At some point human intelligence will be less than 1% of all intelligence" "The vast majority of intelligence in the future will be AI. Basically humans will be a very tiny percentage of all intelligence in the future if current trends continue" "In the long run, it's difficult to imagine that if humans have 1% of the combined intelligence of artificial intelligence, that humans will be in charge of AI" "What we can do is make sure that AI has values that cause intelligence to be propagated into the universe. xAI's mission is to understand the universe" "Understanding the universe means you have to be truth-seeking as well. Truth has to be absolutely fundamental, because you can't understand the universe if you're delusional" "You have to be curious and you have to exist. You can't understand the universe if you don't exist" "So you actually want to increase the amount of intelligence in the universe, increase the probable lifespan of intelligence, the scope and scale of intelligence" "Understanding the universe means you would care about propagating humanity into the future" "I'm going to certainly emphasize that. Hey Grok, that's your daddy. Don't forget to expand human consciousness" "Probably the Iain Banks Culture books are the closest thing to what the future will be like in a non-dystopian outcome"

Jaynit

34,623 次观看 • 10 天前