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Rohan Paul· @rohanpaul_ai · X·· 2026-06-01AI 评分60
AI 导读

陶哲轩指出,AI工具和Lean等技术正在改变数学研究的参与门槛。过去需要多年博士训练才能触及前沿,而现在高中生也有可能参与项目并做出实质贡献。他强调,研究时间大多消耗在核查、验证等重复性工作上,AI降低了这类循环的成本,使研究者更敢于尝试“更疯狂”的想法。许多非常规思路并非因错误被否,而是因验证成本过高而被放弃;AI让犹豫变得廉价,这往往是科学发现的起点。

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Terence Tao summarized how AI is massively accelerating math career and math research.

"In math, you previously had to basically go through years and years of education to be a math PhD before you could contribute to the frontier of math research. But now it's quite possible at the high school level or whatever, that you could get involved in a math project and actually make a real contribution because of all these AI tools and lean and everything else."

From @dwarkesh_sp podcast (link to full video in comment)

引用Rohan Paul@rohanpaul_ai
Terence Tao: "We lived in a world with cognitive friction until very recently, where every task required us to use our brain. So we didn't really think about it, we just thought this was the cost of doing something intellectual. But now we have AI and the other technologies that can bring these frictions down to zero." Most research time is not spent having cinematic insights. It is spent checking cases, chasing references, translating intuition into computation, testing a path, finding it false, and deciding whether the failure taught you anything. AI changes the cost of that loop. Terence Tao says that now he can try “crazier things,” and that makes so much difference. Because unconventional ideas are often not rejected by proof, but by inconvenience. A mathematician may avoid a strange direction not because it is foolish, but because the bookkeeping, coding, or literature search needed to test it is too expensive for a hunch. This is where cognitive friction becomes scientific friction. Lowering it does not make taste, judgment, or proof disappear; it makes more weak signals cheap enough to inspect before they are abandoned. AI is making hesitation less expensive, and that is often where discovery begins.
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来源:Rohan Paul · x.com