OpenAI says a general-purpose reasoning model found a construction disproving the conjectured upper bound in Erdős's planar unit-distance problem. Mathematicians reviewed the proof, but the ML community raises questions about methodological transparency.
An OpenAI general-purpose reasoning model has independently solved the planar unit distance problem — a famous open geometry question posed by Paul Erdős in 1946. External mathematicians verified the proof, marking the first time AI has autonomously solved a major open problem in mathematics.
An OpenAI general-purpose reasoning model independently disproved the Erdős unit distance conjecture — a central problem in discrete geometry open since 1946. This marks the first time in history that an AI has autonomously solved a prominent open math problem, verified by independent mathematicians including Princeton's Noga Alon.
Google DeepMind unveiled an AI Co-Mathematician system — a multi-agent Gemini-based framework scoring 48% on FrontierMath Tier 4, the highest ever for any AI. AlphaEvolve improved lower bounds on five Ramsey numbers, including R(3,13) whose previous record had stood for 11 years.
Fields Medal-winning mathematician Timothy Gowers tested ChatGPT 5.5 Pro on open math problems and found it produced PhD-level proofs in about an hour, warning that mathematical research faces an imminent 'crisis' at the current rate of AI progress.
The technique GPT-5.4 Pro used to solve Erdos Problem 1196 has been applied to other problems, including another conjecture unsolved for 60 years.
The subreddit jumped straight past the headline and into the hard question: was this finally something other than pattern replay? A Scientific American report on a 23-year-old using GPT-5.4 Pro on a 60-year-old Erdos problem sparked debate over novelty, expert cleanup, and whether messy model output can still contain a real mathematical idea.
HN read this math story less as another "AI did it" headline and more as a case where a model pointed at a route humans had not tried. The part that stuck was the expert cleanup work after the GPT-5.4 Pro draft, not the one-shot prompt itself.
This is the kind of numeric jump that makes multi-agent research hard to ignore. Together says EinsteinArena agents raised the 11-dimensional kissing number lower bound from 593 to 604 and had already logged 11 new SOTA results on open problems by April 11.
A March 28 essay on the Hamilton-Jacobi-Bellman equation drew Hacker News attention by showing how continuous-time control theory connects reinforcement learning, optimal control, and diffusion models.
A heavily discussed HN post focused on Epoch AI’s confirmation that GPT-5.4 Pro helped solve one FrontierMath Open Problems combinatorics challenge, shifting attention from benchmark scores toward expert-verified research workflows.
OpenAI said on February 20, 2026 that its theorem-proving model produced proof attempts for all 10 research-level First Proof problems. After expert feedback, the company believes at least five attempts are likely correct, while some remain under review and the attempt for problem 2 now appears incorrect.