korrents
Terence Tao

What Terence Tao thinks about AI and science

@terence-tao · 54 positions · On ppll ↗

Terence Tao did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

Filter AI and science · Newest first
Topic
All 54mathematics 34AI and science 12formal proof 3physics 3AI agents 2education 2LLMs 2peer review 2AI alignment 1
11 more topics
AI and human skill 1AI and jobs 1coding agents 1cryptography 1curiosity 1Google 1measuring intelligence 1metascience 1quantum mechanics 1reinforcement learning 1scaling laws 1
Sort
NewestOldest

Only Terence Tao on AI and science. See everyone on AI and science

12 dated positions, 2025 to 2026, in their own words. Our reading of what Terence Tao has said — not written or endorsed by them.

  1. Our readingCurrent AI4Math systems largely operate as solvers of isolated, well-defined proofs rather than as researchers that expand mathematical knowledge.

    Their wordsDespite these strides, we argue that current AI4Math systems still largely operate as solvers, excelling at isolated, well-defined proof generation rather than as researchers capable of expanding the boundaries of mathematical knowledge.

    ↗From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier (with 18 co-authors)arxiv.org All 4 from this paper

  2. 4 months earlier

  3. Our readingAI has driven the cost of generating scientific ideas to almost zero, and just as with cheap communication before it, that by itself creates no abundance.

    Their wordsSo, I think AI has basically driven the cost of idea generation down to almost zero in a very similar way to how the internet drove the cost of communication down to almost zero, which is an amazing thing, but it you know, it it it doesn't make it doesn't create abundance by itself.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 1st of 24 in this recording

  5. Our readingThe structures of science now have to change, because the scarce thing is no longer proposing theories but verifying and evaluating the thousands anyone can now propose.

    Their wordsSo, we're now in a situation where suddenly people can generate thousands of theories for a given scientific problem. And now we have to to verify them, evaluate them and this is something which we we have to to change our structures of science to actually sort this out.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 2nd of 24 in this recording

  7. Our readingAI excels at breadth and human experts at depth, which makes them complementary and makes today's depth-focused way of doing science the wrong shape.

    Their wordsYeah, so they excel at breadth and humans excel at depth. Um like human experts at least. Yeah, so um I think they're very complementary. Um but our current uh way of doing math and science is focused on depth because that that's where the human uh expertise cuz humans can't do breadth.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 7th of 24 in this recording

  9. Our readingOn small tasks he can check himself, he catches about as many of the AI's errors as it catches of his.

    Their wordsSo, they they they still make mistakes, but but um um I've I've tested these tools, you know, on on on on um like little tasks that I can do and and sometimes they pick up errors I make, sometimes I pick up errors that they make. It's it's about a tie right now.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 9th of 24 in this recording

  11. Our readingOn any given problem an AI tool succeeds maybe one or two percent of the time; the headline results are what running it at scale and picking the winners looks like.

    Their wordsUh but whenever we do a systematic study, um any given problem, an AI tool has a success rate of maybe 1 or 2%. Uh it's just that it's just that they can apply at scale and and you just pick the winners, it looks great.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 12th of 24 in this recording

  13. Our readingAI has made his papers richer and broader, but not deeper.

    Their wordsUh yeah, so it's it's made papers sort of richer and broader, but not necessarily deeper.

    ↗Terence Tao – How the world’s top mathematician uses AIyoutube.com 14th of 24 in this recording

  14. 9 months earlier

  15. Our readingSolving one Olympiad problem with three days of Google's server time shows what is possible, but the approach does not scale.

    Google

    Their wordsYeah, these are great work that shows what's possible. The approach doesn't scale currently. Three days of Google's server time can solve one high school math format there. This is not a scalable prospect, especially with the exponential increase as the complexity increases.

    ↗Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI | Lex Fridman Podcast #472youtube.com 7th of 20 in this recording

  17. Our readingAI could compete with human mathematicians once it acquires a mathematical sense of smell: knowing which way of splitting a problem makes it easier rather than harder.

    mathematics

    Their wordsVery rarely do you transform into a simpler problem. So if they can pick up a sense of smell, then they could maybe start competing with a human level of mathematicians.

    ↗Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI | Lex Fridman Podcast #472youtube.com 8th of 20 in this recording

  19. Our readingHis prediction that research-level mathematics papers would be written in collaboration with AI by 2026 has already come true.

    mathematics

    Their wordsThere are certainly math results which could only have been accomplished because there was a human authentication and an AI involved, but it's hard to disentangle credit. I mean, these tools, they do not replicate all the skills needed to do mathematics, but they can replicate some non-trivial percentage of them, 30, 40%, so they can fill in gaps.

    ↗Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI | Lex Fridman Podcast #472youtube.com 10th of 20 in this recording

  21. Our readingThis decade, AI could propose a conjecture connecting two things nobody thought were related, with a real chance of it being correct and meaningful.

    Their wordsYeah, this decade I can see it making a conjecture between two things that people would thought was unrelated.

    ↗Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI | Lex Fridman Podcast #472youtube.com 11th of 20 in this recording

  23. Our readingCurrent AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect.

    physics

    Their wordsThe dream is you just feed it all this data, and this is here is a new patent that we didn't see before, but it actually, even the current state of the art even struggles to discover old laws of physics from the data.

    ↗Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI | Lex Fridman Podcast #472youtube.com 12th of 20 in this recording