Terence Tao
Article
Terence Tao is a recurring person in the Astral Codex Ten archive, appearing 5 times across 5 issues between April 01, 2022 and July 08, 2025. The archive places it in contexts such as “Terence Tao was the youngest ever professor at UCLA”; “Hassabis also reveals that he’s asked Terence Tao about working on AI alignment”; “So that was what I would be advocating to you know the Terence Tao’s of this world, the best mathematicians”. It most often appears alongside DeepMind, Demis Hassabis, GPT-3.
Metadata
- Category: People
- Mention count: 5
- Issue count: 5
- First seen: April 01, 2022
- Last seen: July 08, 2025
Appears In
- The Low-Hanging Fruit Argument: Models And Predictions
- Links For June
- Why Not Slow AI Progress?
- Your Book Review: How Language Began
- Now I Really Won That AI Bet
Related Pages
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- DeepMind (2 shared issues)
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- Demis Hassabis (2 shared issues)
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- GPT-3 (2 shared issues)
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- Reddit (2 shared issues)
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- Shane Legg (2 shared issues)
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- Texas (2 shared issues)
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- Wikipedia (2 shared issues)
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- 4o (1 shared issues)
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- 80,000 Hours (1 shared issues)
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- 80,000 Hours’ Guide To Working In AI Policy And Strategy (1 shared issues)
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- @a_centrism (1 shared issues)
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- @amplituhedron (1 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
I don’t really know how to test these claims, especially the second. But for what it’s worth, John von Neumann was the youngest ever lecturer at the University of Berlin, and Terence Tao was the youngest ever professor at UCLA.
4: DeepMind on AGI (podcast transcript). Co-founder Shane Legg says that "maybe we will have an AGI in a decade". Other co-founder Demis Hassabis says "I wouldn't be super surprised in the next decade or two." Hassabis also reveals that he's asked Terence Tao about working on AI alignment (no sign Tao is interested).
Inline links: DeepMind on AGI
Potentially. I always imagine that as we got closer to [superintelligence] , the best thing to do might be to pause the pushing of the performance of these systems so that you can analyze down to minute detail exactly and maybe even prove things mathematically about the system so that you know the limits and otherwise of the systems that you're building. At that point I think all the world's greatest minds should probably be thinking about this problem. So that was what I would be advocating to you know the Terence Tao’s of this world, the best mathematicians. Actually I've even talked to him about this—I know you're working on the Riemann hypothesis or something which is the best thing in mathematics but actually this is more pressing.
Mathematician Terence Tao (96,000 = 0.19 Chomskys)
Inline links: Terence Tao
I think this thesis has done well so far. So far, every time people have claimed there’s something an AI can never do without “real understanding”, the AI has accomplished it with better pattern-matching. This was true back in 2020 when GPT-2 failed to add 2+1 and Gary Marcus declared that scaling had failed and it was time to “consider investing in different approaches” (according to Terence Tao, working with AIs is now “on par with trying to advise a mediocre, but not completely incompetent, static simulation of a graduate student”). I think progress in AI art tells the same story.
Inline links: Gary Marcus declared