Timothy Gowers @wtgowers on Twitter / X

An OpenAI model has disproved a central conjecture in discrete geometry

An OpenAI model solved the 80-year-old unit distance problem, disproving a major conjecture in discrete geometry and marking a milestone in AI-driven mathematics.

AI contributions to Erdős problems

A community database for the problems on the erdosproblems.com site - teorth/erdosproblems

Michael Truell on Twitter / X

We believe Cursor discovered a novel solution to Problem Six of the First Proof challenge, a set of math research problems that approximate the work of Stanford, MIT, Berkeley academics. Cursor's solution yields stronger results than the official, human-written solution.…— Michael Truell (@mntruell) March 3, 2026

Shouqiao Wang on Twitter / X

I solved 6 open Erdős problems in 5 days, using @OpenAI GPT-5.6 Sol.I have a math background, but the Codex workflow I used does not require deep mathematical knowledge.Here’s exactly how I approached it, including my prompts 🧵— Shouqiao Wang (@Qiaoqiao2001) July 22, 2026

Ten advances in mathematics and theoretical computer science

OpenAI shares new results on long-standing open problems in mathematics and theoretical computer science, including advances in geometry, cryptography, and complexity.

Thomas Bloom on Twitter / X

Big news! (And not really my area, but yes, I would rank this as bigger than the unit distance counterexample. Maybe not bigger than a proof of unit distance would have been, but in terms of constructions, this is big.) https://t.co/VDRti1HZ6Z— Thomas Bloom (@thomasfbloom) August 1, 2026

98 out of 100. That's how many advanced maths problems current AI models managed to solve in an international benchmark in Leipzig. One of the two remaining problems? A simplified version of a… | Czech Technical University in Prague | 11 comments

98 out of 100. That's how many advanced maths problems current AI models managed to solve in an international benchmark in Leipzig. One of the two remaining problems? A simplified version of a combinatorics problem solved by researchers from the Faculty of Information Technology CTU in Prague. Alexander Clifton, Daniela Černá and Jan Volec, together with Bartołomiej Kielak from Universität Leipzig , found the solution to a simplified version of the long-standing open problem of breaking triples with permutations. The problem was later included among the 100 tasks used to test how today's AI models perform in advanced mathematics. While AI came remarkably close, this was one of the problems it couldn't solve on its own. A nice reminder that mathematical creativity and abstract reasoning still leave some room for humans. 🧠 🔗 Read the full story in the comments. | 11 comments on LinkedIn

Amateur armed with ChatGPT 'vibe-maths' a 60-year-old problem

A ChatGPT AI has proved a conjecture with a method no human had thought of. Experts believe it may have further uses

AI Has Solved One of Math’s $1 Million Millennium Prize Problems | Quanta Magazine

Mathematicians at OpenAI showed that the Navier-Stokes equations, which describe how fluids flow, can sometimes “blow up.” But the massive result is not without controversy.

Can AI replace mathematicians? Vienna researchers weigh in

In September, OpenAI announced that some 10,000 AI agents partially 'solved' the Navier–Stokes problem, one of the most prestigious open challenges in mathematics. University of Vienna mathematicians Nathanaël Berestycki and Vera Fischer agree that the field will never be the same, but argue that maths is far more than producing proofs at speed.

OpenAI's Unreleased Model Astra Solves Ten Major Open Mathematics Problems

Math is hard.

Noam Brown on Twitter / X

And yes we did try other major problems without success. Sadly no Millennium Prize problems (yet).But also, we didn’t spend a lot on each problem. It’s possible to push test-time compute much further.— Noam Brown (@polynoamial) August 1, 2026

Terence Tao (@tao@mathstodon.xyz)

I wrote recently about how the collection of good, fruitful open problems is now being mined in a non-renewable fashion, leading to the potential scenario of these problems becoming scarce. This may seem unintuitive at first, since the set of possible problems one could ask is infinite. Perhaps the following analogy can help: a country or region can suffer a critical shortage of drinking water while simultaneously being surrounded by a massive ocean. One can easily generate any number of open problems in mathematics at will, such as working out the 10^10^10th digit of pi. But the vast majority of such problems are not worth focusing attention on: they show no particular propensity to reveal any further insights or connections to other questions, or may either be too easy or too impossible relative to known techniques to learn anything from the exercise. (1/4)