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.@GoogleDeepMind presented AlphaEvolve, a coding agent for math, computing and general-purpose algorithm discovery. It's powered by: - Ensemble of top Gemini models to enhance creativity and - Automated evaluators to verify solutions. AlphaEvolve is an evolutionary system - its elements work in a loop, constantly trying out changes to the code, checking what works better, and keeping the best options to optimize algorithms. Details 🧵
1. The working process: - Firstly, you provide AlphaEvolve an initial version of the code and an evaluation function. - AlphaEvolve uses Gemini models to suggest code improvements. Gemini Flash maximizes the breadth of ideas, and Gemini Pro gives critical depth to suggestions. - Every new version of the code is scored by running it through the evaluation function. The best-performing ones are saved and reused for future suggestions. - The process repeats and the code gets better and better.
2. Here's what AlphaEvolve has already achieved: - It created a better scheduling system for Google’s data centers. - Simplified computer hardware design, removing unnecessary bits and designing faster arithmetic circuit for matrix multiplication. This is applied in upcoming Google's Tensor Processing Unit (TPU). - Helped speed up training of Gemini models. - Achieved up to a 32.5% speedup for the FlashAttention kernel implementation. - Explored new solutions to open math problems👇
Paper: <a target="_blank" href="https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/AlphaEvolve.pdf" color="blue">storage.googleapis.com/deepmind-media…</a> Blog: <a target="_blank" href="https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/" color="blue">deepmind.google/discover/blog/…</a>