Let me explain in simple terms what this OpenAI Math repo is about I cloned it and started going through it carefully. There's still more to check, but this is what I have so far OpenAI has a new internal model and wanted to know how good it really is at math Normal math benchmarks were already too easy for it, so they gave it open research problems that professional mathematicians haven't solved, some of them stuck for decades They gave it around 4,000 problems. The model spent about 3 hours on each one and wrote its answers as real papers After filtering, they ended up with 722 papers grouped into 372 results, some claim to solve very well known problems The catch is that a long proof can hide a small mistake nobody sees, and checking one paper by hand can take an expert months That's where Lean comes in. Lean is a programming language where you write the proof step by step and the computer checks every step If it compiles, the logic is correct. Think of a teacher who never gets tired and never skips a line More than half of the results come with a Lean version I searched the Lean code for the usual shortcuts (sorry, fake axioms) and found none Those are the strongest results in the repo. The rest is basically "the AI says it works" and still needs humans to review it OpenAI itself marks the formalizations as unchecked One more catch. Lean checks that the proof is correct, but someone still has to confirm that the statement written in Lean is the same question as the famous problem Write the question slightly wrong and you can perfectly prove the wrong thing People are already finding cases where the Lean only covers part of what the paper claims Repo: