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)
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.