Number theorist at UMontreal, author of “The Distribution of Prime Numbers” https://xitter.cf/t.co/5shPp0YcvW. Mastodon: @iteratedlog@mathstodon.xyz

Montréal, Québec
Joined October 2010
I’ve written a guest post on Terry Tao’s blog about the challenges science is facing due to the rise of AI and some thoughts about how we can address them. Many thanks to Terry for hosting me. terrytao.wordpress.com/2026/…
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Dimitris Koukoulopoulos retweeted
I expect the big AI labs will soon stop dumping hundreds of papers. They’ve proved their point. The dust will settle and we’ll be left with an amazing tool to assist us with our research. Public access is the key. We need it free. terrytao.wordpress.com/2026/…
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We need tools for AI-assisted science that are fully secure and aligned with the goals of the scientific community. The only way to guarantee this is to build them ourselves. A "CERN for AI-assisted science" would be a major step in this direction: terrytao.wordpress.com/2026/…
Mathematicians need to build an LLM infrastructure capable of supporting ambitious research projects in a safe environment, one that guarantees recognition, transparency, and confidentiality, and is compatible with training new generations of mathematicians. Indeed: (1) It’s an exciting time to be a mathematician. LLMs can turbocharge our discipline. I can think of two or three ambitious projects that go well beyond conjectures and famous lists of problems, with genuine mathematical depth and significant impact outside mathematics. But I wouldn’t trust ChatGPT with even the vaguest description of these projects. There are simply no adequate guarantees of confidentiality, transparency, or control over how research ideas are handled on these platforms. And I have no reason to believe Anthropic is any different, by the way. (2) The way OpenAI has decided to go about Tuesday’s drop — with no meaningful effort to acknowledge the human mathematical contributions underlying the results, no engagement with the established processes of peer review, and no transparency about training datasets, prompts, and procedures — is extraordinarily damaging to the pipeline that produces new mathematicians. Why would the next generation of talented young people devote their lives to learning and creating mathematics if the future we are offering them consists largely of checking machine-generated proofs? Eradicating humans from mathematics today, and from STEM tomorrow, would be disastrous for human culture. And I fear that OpenAI’s drop has put mathematics on precisely that path. Which brings me back to where I started: we need to build LLM infrastructure that is safe for research, mentoring, and peer review, under the control of the mathematical community, and outside the control (and potential predation) of OpenAI and its frenemies.
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Dimitris Koukoulopoulos retweeted
Really nice article. If hard math problems are indeed good "food for the shoggoth" (RL material), there seems no reason for AI companies not to just allow a large group of mathematicians access to internal models, to give more hard questions for the models to solve
I expect the big AI labs will soon stop dumping hundreds of papers. They’ve proved their point. The dust will settle and we’ll be left with an amazing tool to assist us with our research. Public access is the key. We need it free. terrytao.wordpress.com/2026/…
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I expect the big AI labs will soon stop dumping hundreds of papers. They’ve proved their point. The dust will settle and we’ll be left with an amazing tool to assist us with our research. Public access is the key. We need it free. terrytao.wordpress.com/2026/…
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Dimitris Koukoulopoulos retweeted
Replying to @lreyzin
We've been given a very powerful tool. We still need to point it to interesting problems and work with it. This is more analogous to the supercollider in physics that confirms theories and intuitions. Our math experiments will need to be interpreted, and lead us to new insights.
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Dimitris Koukoulopoulos retweeted
I realize @AcerFur is being ironic, but the popularity of the idea that AI "merely explores the convex hull" mystifies me. Why wouldn't it be more like the subgroup generated by existing mathematical knowledge? (That's also a metaphor -- I'm not saying there's a group structure.)
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Dimitris Koukoulopoulos retweeted
My dream had always been to prove beautiful theorems as the AI agents unloaded my dishwasher. Well, it went the wrong way... 😂
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Χρειαζόμαστε θεσμικές λύσεις για ελεύθερη πρόσβαση των επιστημόνων σε εργαλεία αιχμής τεχνητής νοημοσύνης. Σε άρθρο μου στην Κ προτείνω τη δημιουργία της κατάλληλης υποδομής - ενός νέου CERN - για τον εκδημοκρατισμό της πρόσβασης στην ΤΝ. kathimerini.gr/world/5644801…
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This article’s perspective on the future of humans in math is very closely aligned (!) with my thinking.
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Dimitris Koukoulopoulos retweeted
I was part of a group that met last week to try to propose recommended changes to the structure of math PhD programs in an age of AI. Our report, together with a collection of related resources, is now available here: cmsa.fas.harvard.edu/aimathp…
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Very powerful address to the UN Security Council by Yoshua Bengio about AI safety.
I was invited to address the @UN Security Council this afternoon to discuss the unprecedented threat posed by uncontrolled frontier AI agents. Humanity has summoned the courage and wisdom to manage catastrophic risks before. This is one of those moments, far bigger than any personal, commercial, or national interest. The choices we make about this technology today will shape generations to come. We must act now.
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Dimitris Koukoulopoulos retweeted
Martin Hairer, one of the other members of AGMAI (the advisory group on mathematics and AI), has written a post on the Proofs and Prompts blog that will I hope clarify what our purpose is. The rest of the blog is highly recommended too. proofsandprompts.com/2026/09…
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Dimitris Koukoulopoulos retweeted
I’ve had several people ask me about this paper, so background 🧵 Radchenko–Wheeler, “Real quadratic fields and finite quantum dilogarithms I” (arxiv.org/abs/2609.21892). This result is amazing. They prove that certain special values of a transcendental function are actually algebraic. The goal of “explicit class field theory” is to construct algebraic numbers (numbers that are roots of polynomials with coefficients in ℤ), and ultimately abelian extensions of number fields, by evaluating transcendental functions at special points. It traces back to Hilbert's 12th problem. Ex 1: For ℚ, you have z = exp(2πix) at rational x. Clearly algebraic since z^n=1 if x=k/n. Ex 2: For imaginary quadratic fields, you have "complex multiplication". Take τ in the upper half-plane and Λ = ℤ + τℤ. Then ℂ/Λ is an elliptic curve. At imaginary quadratic (“CM”) values of τ, the transcendental modular function j(τ) (j-invariant) is an algebraic integer. Hilbert called CM "not only the most beautiful part of mathematics but also of the whole of science." If τ is real, this breaks completely because Λ = ℤ + τℤ is dense in ℝ (despite still being rank 2 as a ℤ-module). So ℂ/(ℤ+τℤ) is not a nice complex torus anymore and not an elliptic curve. This is one reason Hilbert’s 12th problem gets nasty immediately after ℚ and imaginary quadratic fields and is still almost totally open. (... in the Archimedean case. The p-adic case was proven by @samit_dasgupta and Kakde.) Stark and Shintani predicted that certain analytic quantities attached to real quadratic fields ("Stark units") should nonetheless be algebraic and generate abelian extensions. These can be written in terms of special values of Faddeev’s modular quantum dilogarithm, or a function Appleby, Kopp and I called "ש" (Shin), in homage to Shintani. Quantum dilogarithms are analytic objects, but are expected to satisfy special polynomial identities at certain special points. In our paper on Zauner's conjecture (arXiv:2501.03970), we gave a very explicit quadratic identity that they should satisfy ("the twisted convolution conjecture"), which, together with some more detailed conjectures of Stark, would prove Zauner in every dimension. Radchenko and Wheeler prove that the quantum dilogarithm indeed satisfies polynomial identities at certain special points. They also prove explicitly the twisted convolution conjecture for the case of the principal ideal (the admissible pair (d, ⟨1,1-d,1⟩) in the language of arXiv:2501.03970).  They claim the general case as well, though they omit the proof. Very interestingly, they prove the algebraicity by showing that the quantum dilogarithm maps to a fusion category, and since fusion categories obey "Ocneanu rigidity" they must be algebraic. Rigidity says, roughly, there are only finitely many equivalence classes with fixed fusion data and no continuous deformations. Because the structure constants solve polynomial equations over an algebraic field, that forces them into ℚ̅. Specifically, they say they "categorify Izumi fusion rings", but I don't know what that means and I look forward to understanding this better. Although they have proven algebraicity, they have not actually proven that their algebraic numbers are the "correct" ones, in the sense that "correct" Stark units should live in a specific field extension and have specific transformation properties under the action of the Galois group. This is left open. The consequences for Zauner's conjecture are: It's still completely open for any infinite family! To prove it, you would at least need to prove that there is a Galois automorphism in Gal(ℚ̅/ℚ) that takes the quantum dilogarithm special values to points on the unit circle. You might also need to prove some properties of the Galois group action; I will need to read this to understand it better. Congrats to the authors on a wonderful result!
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There is a closely related (and complementary) proposal put forward last year in Bologna about creating an AI institute in the EU. I'd like to thank Pierluigi Contucci for bringing it to my attention. I have signed the petition and urge you to do the same: change.org/p/a-manifesto-for…
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Dimitris Koukoulopoulos retweeted
Replying to @rperezmarco
I think SAIR is a fantastic initiative. Acknowledging that LLM are going to be a basic math research infrastructure, the next step is developing that kind of infrastructure outside of for-profit dynamics. We cannot leave access to a basic infrastructure to companies that respond only to profit. It is crucial to preserve academic freedom and the very notion of basic science. Folks, OpenAI’s interest in math is merely commercial, it’s a matter of advertising and PR (and they played it poorly), you can’t imagine a future for math where they control who does what in math. Also, I keep being amazed by people spouting hate towards the likes of Tao or Villani, like they are just any other folk commenting on math research. Seriously.
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Dimitris Koukoulopoulos retweeted
Replying to @aryehazan
The argument has to be that we’ve glimpsed a sliver of everyone’s future, so slow down for your sake, not ours.
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Dimitris Koukoulopoulos retweeted
Mathematician Terence Tao: "we have to slow down AI. the pace is insane, and there's no reason to be this fast — no reason at all" It's amazing how willing we are to change everything without any idea what happens afterward These are extremely nonlinear dynamics
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