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📁 Sam Altman says the real risk is speed, because this technology is only three years old and already the fastest adopted in history. What can cure diseases can also be misused and the tension rises when jobs change faster than society can adapt. New jobs will come, but... show more

Jon Hernandez

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91,611 görüntüleme • 8 ay önce •via X (Twitter)

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Sam Altman warns that AI is spreading faster than any technology in history. He fears society may struggle to keep up as jobs shift at high speed. He urges a responsible rollout so people have time to adapt and give feedback. He believes better work will emerge, but the transition’s pace is the real risk.

Sam Altman warns that AI is spreading faster than any technology in history. He fears society may struggle to keep up as jobs shift at high speed. He urges a responsible rollout so people have time to adapt and give feedback. He believes better work will emerge, but the transition’s pace is the real risk.

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📁 Sam Altman, CEO of OpenAI, says the problem with AI is not if it works. It is what happens when it does. Because curing disease is not enough. The real question is: what do you do when you are no longer needed?

📁 Sam Altman, CEO of OpenAI, says the problem with AI is not if it works. It is what happens when it does. Because curing disease is not enough. The real question is: what do you do when you are no longer needed?

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The Economist asks why China and America see AI so differently. The answer is bigger than technology. It is psychology. In China, optimism about AI runs from government policy to companies to ordinary workers. People know disruption is coming. They know jobs will change. They know some industries will disappear. But the instinct is still: build first, adapt fast, solve the problems as they appear. In America, the instinct increasingly runs the other way: fear the disruption, litigate it, regulate it, politicize it, build barriers around it, and then call the barriers “responsible innovation.” The difference is deeper than AI. China still has a strong social belief that technology can make life better and that society can absorb change. America increasingly treats every technological shift as another mechanism through which ordinary people may be abandoned by the system. That is why one society sees robots and asks: “How do we use them?” while the other asks: “Who is going to lose their job?” One is operating from confidence. The other from accumulated distrust. And that matters far more than any benchmark. You cannot lead a technological revolution if your society has already decided that every new technology is another threat waiting to happen. China is not fearless because disruption does not hurt. China is less afraid because it still believes disruption can be survived. America’s real problem is not that it fears AI. It is that too many Americans no longer trust their own system to protect them from the future. The real AI gap may not be compute. It may be confidence in the future.

The Economist asks why China and America see AI so differently. The answer is bigger than technology. It is psychology. In China, optimism about AI runs from government policy to companies to ordinary workers. People know disruption is coming. They know jobs will change. They know some industries will disappear. But the instinct is still: build first, adapt fast, solve the problems as they appear. In America, the instinct increasingly runs the other way: fear the disruption, litigate it, regulate it, politicize it, build barriers around it, and then call the barriers “responsible innovation.” The difference is deeper than AI. China still has a strong social belief that technology can make life better and that society can absorb change. America increasingly treats every technological shift as another mechanism through which ordinary people may be abandoned by the system. That is why one society sees robots and asks: “How do we use them?” while the other asks: “Who is going to lose their job?” One is operating from confidence. The other from accumulated distrust. And that matters far more than any benchmark. You cannot lead a technological revolution if your society has already decided that every new technology is another threat waiting to happen. China is not fearless because disruption does not hurt. China is less afraid because it still believes disruption can be survived. America’s real problem is not that it fears AI. It is that too many Americans no longer trust their own system to protect them from the future. The real AI gap may not be compute. It may be confidence in the future.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

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📁 Geoffrey Hinton says the impact of AI will be radical and deeply uncertain. Many jobs will disappear and there is no guarantee new ones will replace them. AI will massively boost productivity, but the real issue is not technological. It is political. How wealth is distributed when work is no longer required. More productivity does not guarantee a better future. Without systemic change, it could mean the opposite.

📁 Geoffrey Hinton says the impact of AI will be radical and deeply uncertain. Many jobs will disappear and there is no guarantee new ones will replace them. AI will massively boost productivity, but the real issue is not technological. It is political. How wealth is distributed when work is no longer required. More productivity does not guarantee a better future. Without systemic change, it could mean the opposite.

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📁 Sam Altman says the real Turing test is when AI can do science, and with GPT-5 we’re already seeing the first signs. In two years, these models will make key discoveries that transform the world, because scientific progress is what drives humanity forward.

📁 Sam Altman says the real Turing test is when AI can do science, and with GPT-5 we’re already seeing the first signs. In two years, these models will make key discoveries that transform the world, because scientific progress is what drives humanity forward.

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📁 Dario Amodei, CEO of Anthropic, says AI will disrupt jobs faster and broader than anything before. Some roles, even software engineers, may shrink as models automate entire workflows. The real question is not which jobs disappear. It is whether we create new ones in time.

📁 Dario Amodei, CEO of Anthropic, says AI will disrupt jobs faster and broader than anything before. Some roles, even software engineers, may shrink as models automate entire workflows. The real question is not which jobs disappear. It is whether we create new ones in time.

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Dario Amodei says AI disruption isn't different in kind from past technological shifts, but it's deeper and faster Unlike factories or the internet, AI hits multiple entry points at once The worry is we're eliminating jobs faster than we can adapt people or create new ones

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Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

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Holy moly, Lyria 3 is mindblowing. Not necessarily because it can now also create songs like Suno, but because it perfectly creates songs in languages other than English. I had it create a German song in the style of Hans Eisler as an example – and not only is there no accent, but the German is perfect, and the music-to-lyrics ratio is outstanding.

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The Father of HBM, Kim Jung-ho says physical AI is really a memory problem, because a self-driving car can't react faster than its memory can recall what it learned, and the stakes are: it cannot be a second late on the brakes. "Physical AI is memory AI." "The car crashes as it drives, remembers it all, and learns from it." "What's harder is the learning and reasoning must be real-time. A self-driving car can't hit the brakes a second late." "So here not just capacity, but speed matters too. Memory's speed." "Future memory will lead the AI revolution, and there it's speed and capacity. Speed is bandwidth, capacity is stacking. That's how I see it." ______ More from his lecture here:

The Father of HBM, Kim Jung-ho says physical AI is really a memory problem, because a self-driving car can't react faster than its memory can recall what it learned, and the stakes are: it cannot be a second late on the brakes. "Physical AI is memory AI." "The car crashes as it drives, remembers it all, and learns from it." "What's harder is the learning and reasoning must be real-time. A self-driving car can't hit the brakes a second late." "So here not just capacity, but speed matters too. Memory's speed." "Future memory will lead the AI revolution, and there it's speed and capacity. Speed is bandwidth, capacity is stacking. That's how I see it." ______ More from his lecture here:

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🚨 SAM ALTMAN: “AI is going to do more of the total thinking than people are … It likely will be quite disruptive to a lot of the current jobs if more of the intellectual horsepower in the world is GPU’s.”

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