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Google DeepMind open-sources AlphaEvolve code and verification notebooks for new math results

·2026.11.05 09:00

Key point

The repository includes a minimal implementation of AlphaEvolve, data for a new upper bound on the matrix multiplication exponent, and verification code for 15 mathematical problems.

Details

  • Google DeepMind has released the source code for AlphaEvolve, an evolutionary algorithm that uses LLMs to discover new mathematical results.
  • The release includes code and data for a new upper bound on the matrix multiplication exponent, verified via a Colab notebook using rational arithmetic.
  • The repository provides verification notebooks for 15 specific mathematical problems where AlphaEvolve found solutions outperforming the state-of-the-art, including circle packing, Heilbronn problems, and cap sets.
  • A minimal implementation of AlphaEvolve is provided in the /src directory, requiring Docker for program evaluation and a Gemini API key for execution.
  • The software is licensed under Apache 2.0, with a disclaimer noting that LLM-generated code is run in a Docker sandbox but still carries inherent security risks.
  • The /omega directory contains gradient-based optimization code at recursion depth 3, which runs 32k steps with 32 random seeds to build a differentiable upper-bound model in JAX/Haiku.
llmopen-sourcegoogle-deepmindalphaevolveevolutionary-algorithmmatrix-multiplicationmathematical-discovery
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