Oxford, England
Joined July 2015
Just came back from playing some guitar, and let me tell you, learn a musical instrument, any of them. From the spoons to a grand piano. Doesn't matter. It's going to change your life. Believe me.
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Conley Index🤝 Flow Categories Landfall Geometry arxiv.org/abs/2610.30993 Joint with Frances Kirwan!
Landfall Geometry Frances Kirwan, Vidit Nanda arxiv.org/abs/2610.30993 [𝚖𝚊𝚝𝚑.𝙰𝚃 𝚖𝚊𝚝𝚑.𝙳𝚂]
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Paper about to drop soon, can't wait!
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To Whom It May Concern: It is fine to mourn the loss of an imperfect system in the face of changes which might introduce another imperfect system. It is less fine to surrender to such despair rather than adapting to the changes.
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Some excellent, practical and timely advice from Etingof on AI use in research mathematics, especially by students: math.mit.edu/~etingof/aiuse.…
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literally all i see when you tell me that your agents are agents trawling the web for hidden alpha
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Saw the flying scotsman today, training error = 0.
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When I was teaching at Yale, Thomas Koberda was a postdoc working with Yair Minsky. Thomas and I got to reconnect two weeks ago at an AMS meeting in DC on “What the heck is a math PhD now?” (My short answer: deeply learning difficult mathematics, being able to orally explain every detail, becoming the human world expert on some (however small) area of mathematical knowledge. Long answer: ams.org/about-us/governance/…) Anyway, we got to chatting over some beers at dinner, and Thomas was much more down on what it all means for mathematics than I was, and we wanted to get to the “bottom” of things; make explicit any assumptions that were underlying our conclusion. We had a very nice chat, not necessarily agreeing on everything, but definitely feeling like we heard each other’s arguments. So the next day, we basically had the conversation again, but this time in a shared Google Doc, at first talking as we type, but eventually just “typing at” each other in silence. We allowed ourselves to interject, to fix what we were saying from the first version, to fact check, to tighten our arguments as much as we saw fit. It was a *wonderful* way to, in good faith, debate/discuss serious topics with serious disagreement. (I would *love* to see other topics discussed this way…) We felt it may be useful to others, so cleaned it up a bit and posted to the arxiv. arxiv.org/abs/2610.14362 I was also contacted by Proofs and Prompts asking for a contribution, so we cross-posted it there. proofsandprompts.com/2026/10… I’m quite eager to hear what people think of the conversation!
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Vidit Nanda retweeted
I am teaching a topics course next semester! (ty Opus 5.5 for the help on the flyer)
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Vidit Nanda retweeted
amid the angst over what human/ai mathematicians can/should do now, i gave a talk at Penn that framed things in terms of four 20th century eigenmathematicians and their stereotypical styles: 1. erdos -- this is what ai has excelled at; shotgunning results, examples & counterexamples, prolific 2. wiles -- go deep & solve the big-name conjecture; this is where we are now w/openai & anthropic's recent works 3. grothendieck -- build the incomprehensible unpredictable ur-theory that cracks something open and exfiltrates to other areas; this is where all ai-enthusiast mathematicians i know are directing their energies; not quite there yet... === but the 4th is not a direction i've seen people discuss & it's where i personally want to dig in... === 4. milnor -- find the connections between deep things and weave a story of such clarity & elegance that it changes the field and how people learn it and use it === this aligns with the "humans will still drive tastes" argument for relevance, which is not yet proven to survive pressure from top models. i suspect that there is, both now and for a spell, room for a creative director to use ai-tools to write the book-of-X (or direct the playlist-of-X) for various values of mathematical X.
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mathematicians asked for this work to be done
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Some personal perspectives on AI x Math: Current models are indeed still better at combining existing ideas than coming up with fundamentally new ones. They primarily explore an "n-iterated ε-neighbourhood" of the existing mathematical literature.
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Vidit Nanda retweeted
Mathematicians are OUTRAGED that their high social status, with its accompaniment of wealth, women, and general extravagance, has been encroached upon by artificial intelligences of humble background.
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Four things: 0/4
Replying to @viditnanda
I was referring to first line “the future of math is lean verification of AI gen. theorems.” sounds kinda scary, no? also, i would love to know your take on the recent papers put out by OAI, what do you think of them?
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Dropping hard-to-read drafts with major results without participating in the journal hunger games is not new (cf Lurie, Perelman,...). OpenAI have just done this at scale. The era of "big conjectures" may end, but the era of "cool theorems" will not. 3/4
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There are big downsides, especially for many routine career aspects (who to hire, who gets prizes, selecting phd topics,...) But the benefit is an infinite-energy collaborator with impossible breadth of knowledge and rapid turnaround times. 4/4
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The future of mathematics is lean verification of AI generated theorems. But can these verifications be trusted? My new startup has developed Lean^2 to verify your verifications. Office: 1700 Riverside Dr., New York, NY Can't wait for you to meet the co-founders!
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Meanwhile, my "internal models" have been struggling to write the fifth paragraph of this wretched introduction for three weeks.
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