FAR Framework Shifts AI Math Research from Solving Problems to Finding Them
dan_fried · x · 2026-08-19
Traditional AI for math focuses on solving given problems, but mathematical discovery also involves deciding which problems are worth solving. A new paper introduces FAR (Find, Attempt, Recommend), a paradigm to scale this process.
How it works:
- Takes a broad research direction as input.
- Find: Scans literature for open conjectures.
- Attempt: Attempts to resolve them at scale.
- Recommend: Filters promising conjecture-resolution pairs for human expert review.
Impact: A pilot run on combinatorics literature surfaced potential resolutions to hundreds of open problems, demonstrating AI's potential to identify, not just solve, mathematical challenges.
Related event: FAR Framework Enables AI Mathematical Discovery, Solving 1977 Conjecture(3 posts)→
More from Research
- Research exposes LLM API vulnerability leaking hidden chain-of-thought — burkov · 2026-08-20
- The Human-or-Machine Issue: Turing-Inspired Reflections — ArtificialOther · 2026-08-20
- Meta Research Challenges Chinchilla Scaling Laws on Data-Compute Interactions — burkov · 2026-08-20
- 14,472 AI citations analyzed: business websites still win 60% of local search citations — gaganghotra_ · 2026-08-20
- LEGO-RL: harness-native reinforcement learning for coding agents — Lego-X · 2026-08-20
- Fourier Neural Operators predict quantum dynamics 10^7x faster than CUDA-Q — AnimaAnandkumar · 2026-08-20