AlphaEvolve helps lower the matrix multiplication exponent ω to below 2.371177
A paper by Alman, Vassilevska Williams and co-authors including DeepMind researchers (arXiv 2608.16884) improved the bound on the matrix multiplication exponent from ω < 2.371339 to ω < 2.371177. AlphaEvolve refined the optimiser used in the laser-method analysis.
Key facts
- ω < 2.371177 (previous: 2.371339)
- Humans reformulated the optimisation problem; AlphaEvolve improved the numerical optimisation
Science result
- Field
- computer-science / algebraic complexity
- Problem
- Matrix multiplication exponent ω
- Result
- New upper bound ω < 2.371177.
- AI system
- AlphaEvolve
- Human role
- Human-led with AI tools
- Verification
- Preprint; bound verifiable from the published optimisation certificates
- Status
- confirmed
What happened
Leading researchers on fast matrix multiplication used AlphaEvolve inside their laser-method pipeline to squeeze out a new record bound.
Why it matters
Progress on ω comes in tiny, hard-won steps. AI now contributes to the asymptotic theory as well as to small concrete algorithms.
Changelog
- 2026-09-29: added post link(s) (1) from Google/DeepMind + math posts pass
- 2026-09-29: created
Related posts (1)
- Pushmeet Kohli: new record for the matrix multiplication exponent ω < 2.371177 with AlphaEvolve Pushmeet Kohli @pushmeet · x · 2026-08-18
Google DeepMind's science VP announced that AlphaEvolve helped lower the upper bound on ω, a central constant of complexity theory.
Related events
- AlphaEvolve: Gemini-powered agent discovers new algorithms ★★★★
- AlphaTensor discovers faster matrix multiplication algorithms, beating Strassen's 1969 record for 4×4 mod 2 ★★★★
Sources (3)
- paperarXiv 2608.16884
- pressAI Weekly: AlphaEvolve helps push matrix multiplication to 2.371177
- officialPushmeet Kohli on X announcing ω < 2.371177
id: 2026-08-17-alphaevolve-matrix-multiplication-exponent · updated 2026-09-29 · open in the interactive timeline