Published: May 14, 2025
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Introducing AlphaEvolve: a Gemini-powered coding agent for algorithm discovery. Itโ€™s able to: ๐Ÿ”˜ Design faster matrix multiplication algorithms ๐Ÿ”˜ Find new solutions to open math problems ๐Ÿ”˜ Make data centers, chip design and AI training more efficient across @Google. ๐Ÿงต

Our system uses: ๐Ÿ”ต LLMs: To synthesize information about problems as well as previous attempts to solve them - and to propose new versions of algorithms ๐Ÿ”ต Automated evaluation: To address the broad class of problems where progress can be clearly and systematically measured. ๐Ÿ”ต

Image in tweet by Google DeepMind

Over the past year, weโ€™ve deployed algorithms discovered by AlphaEvolve across @Googleโ€™s computing ecosystem, including data centers, software and hardware. Itโ€™s been able to: ๐Ÿ”ง Optimize data center scheduling ๐Ÿ”ง Assist in hardware design ๐Ÿ”ง Enhance AI training and inference

We applied AlphaEvolve to a fundamental problem in computer science: discovering algorithms for matrix multiplication. It managed to identify multiple new algorithms. This significantly advances our previous model AlphaTensor, which AlphaEvolve outperforms using its better and

We also applied AlphaEvolve to over 50 open problems in analysis โœ๏ธ, geometry ๐Ÿ“, combinatorics โž• and number theory ๐Ÿ”‚, including the kissing number problem. ๐Ÿ”ต In 75% of cases, it rediscovered the best solution known so far. ๐Ÿ”ต In 20% of cases, it improved upon the previously

Weโ€™re excited to keep developing AlphaEvolve. This system and its general approach has potential to impact material sciences, drug discovery, sustainability and wider technological and business applications. Find out more โ†“ https://goo.gle/3Fci8Ev

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