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The greatest living mathematician just reframed everything we think we know about the mind. Terence Tao. IQ above 200. Youngest gold medalist in Math Olympiad history. Fields Medal winner. His take on AI should stop you cold. Tao: "This whole era of AI is teaching us that our idea...

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Mathematician Terence Tao offers a counterintuitive take: AI doesn't look intelligent because our definition of intelligence was wrong all along. He argues that the entire history of AI has followed a predictable pattern: "The history of AI has been here's a task that only humans can do, like maybe it is read natural language or win at chess or solve a math problem, and then one by one someone finds some AI algorithm that also does that." But every time a machine cracks one of these "uniquely human" tasks, we move the goalposts. The solution never feels like real thinking: "You look at how it's done and it doesn't feel like intelligence. It's, oh, it was some trick. You just cobbled together these neural networks and you ran some algorithm, and we were looking for some elusive intelligent way of thinking, and we don't see it in the tools that actually solve our goals." Tao then flips the problem on its head. What if the issue isn't with the machines, but with us? "But maybe it's actually because intelligence is not what we think it is." He points to large language models as the clearest case. What they do sounds almost embarrassingly simple: "Large language models in particular become very successful, and a lot of what they're doing is just predicting the next token, clicking the next word in a sentence. And that doesn't sound like something which is intelligent." To show why this feels wrong, Tao draws a comparison to how we'd judge a human doing the same thing: "If you ask someone to improvise a speech and they have no preparation, and at every moment they're just saying the next word that comes to their mind, you don't think that this could actually work." And yet it works for LLMs. Which forces an uncomfortable possibility: "Maybe that's actually a lot of what humans do as well."

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A Talk About AI That Will Blow Your Mind. It Did In 1998 When I Attended The Talk. I just found this video from 1998 when I attended this talk by Rupert Sheldrake, Terence McKenna and Ralph Abraham at the University of California, Santa Cruz to explore how machine intelligence might evolve in relation to our own. I never thought I would see this again and it had a great influence on me in the AI I was building in that era and on to today. But ai just found a copy. I certainly did not run around with a VHS recorder so I am blown away that this exists. Now you can see what I saw. At that time, the internet was still young, and artificial intelligence belonged mostly to science fiction. Yet many of the questions we raised then have become part of daily life. In this conversation, it was explored whether intelligence is best understood as logic and computation, or as something embodied, participatory, and alive. Can the mind be reduced to code, or does life itself depend on forms of knowing that no algorithm can contain? AI now outpace us in speed, reach, and memory. Yet the deeper mystery is not how far they can go, but what they reveal about mind and ourselves. Will AI reproduce the limitations of our mechanistic worldview, or might it help us rediscover dimensions of mind that transcend machinery altogether? It's striking how near we now are to the possibilities we once only speculated about. Quantum computing, self-learning systems, large language models very much as Terence describes—and the looming prospect of superintelligence—have moved from the margins to the mainstream. But the heart of the conversation remains just as relevant today, if not more so: what is consciousness, and how might we participate in its unfolding evolution?

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