First Proof is a new benchmark that challenges large language models with ten research‑level mathematics problems, each crafted by leading mathematicians and kept secret until now. It gives you a clear, blind test of whether an AI can crack frontier math, not just textbook exercises. The initiative aims to separate hype from genuine reasoning ability.
Why First Proof Matters for AI Research
The math community has grown uneasy about claims that AI can solve any problem. By focusing on open‑ended conjectures, First Proof forces models to demonstrate true creative reasoning instead of pattern matching. If an AI can’t solve these ten problems, its touted “mathematical reasoning” remains unproven.
Benchmark Design and Problem Scope
First Proof covers four core areas:
- Algebraic geometry – intricate structures that resist simple formulaic solutions.
- Combinatorics – counting problems that explode in complexity.
- Geometric topology – spaces where intuition often fails.
- Ring theory – abstract algebraic systems that test deep logical chains.
Each problem is presented in encrypted form, ensuring a blind test for any participating AI system.
Community Expectations and Impact
Researchers expect the benchmark to become a reference point for funding decisions, curriculum design, and even policy discussions about AI in science. You’ll see labs racing to submit solutions, and a public leaderboard will track progress transparently.
How Researchers and Labs Can Participate
Submission Process
Participating teams receive the encrypted problem set, develop solutions, and submit their proofs for independent verification. All claims must survive peer review before they appear on the leaderboard.
Potential Outcomes
Success would signal that AI has moved beyond narrow problem‑solving toward genuine hypothesis generation. Failure, on the other hand, would reinforce the view that human intuition remains indispensable at the research frontier.
Practitioner Insights
One computational mathematician noted, “From a practitioner’s standpoint, we need a clear signal whether an AI can be trusted to suggest new conjectures or just verify existing ones. First Proof gives us that signal, provided the community treats the results transparently.”
Another senior engineer added, “We’ve built models that can parse papers and extract lemmas. What we lack is a systematic way to gauge whether those lemmas can be stitched into a novel proof. A benchmark like this is exactly the missing piece.”
