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What Terence Tao thinks about AI and science

@terence-tao · 42 positions · 0 changes of mind

Mathematician at UCLA, Fields Medal 2006. Writes at terrytao.wordpress.com.

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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.

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

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

    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

    Google

    Interesting

  3. 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.

    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

    mathematics

    Interesting

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

    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

    mathematics

    Interesting

  7. 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

    Interesting

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

    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

    physics

    Interesting