{"slug": "improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve", "title": "Improving matrix multiplication exponent with optimization and AlphaEvolve", "summary": "Researchers using a machine-learning-guided optimization algorithm called AlphaEvolve have improved the upper bound on the matrix multiplication exponent to ω < 2.371177, surpassing the previous best of 2.371339. The team, including authors from the paper submitted to arXiv on 17 Aug 2026, reformulated the core optimization problem and combined modern optimization techniques with AlphaEvolve to achieve this result.", "body_md": "# Computer Science > Data Structures and Algorithms\n\n[Submitted on 17 Aug 2026]\n\n# Title:Improving the matrix multiplication exponent with modern optimization and AlphaEvolve\n\n[View PDF](/pdf/2608.16884)\n\n[HTML (experimental)](https://arxiv.org/html/2608.16884v1)\n\nAbstract:The current best bounds on the matrix multiplication exponent $\\omega$ are obtained through a refinement of the laser method called combination loss analysis (Duan et al., 2022; Williams et al., 2024; Alman et al., 2025). In this note, we address the optimization problem at the core of this approach and propose several improvements. First, we reformulate the optimization problem allowing us to solve it in a larger setting than was previously possible. Second, we leverage recent advances in machine learning to design a new optimization algorithm for this problem. Finally, we refine the resulting optimization algorithm with AlphaEvolve. Our combined approach yields an upper bound of $\\omega$ < 2.371177, improving the previous best bound of 2.371339.\n\n### Current browse context:\n\ncs.DS\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve", "canonical_source": "https://arxiv.org/abs/2608.16884", "published_at": "2026-08-18 15:28:30+00:00", "updated_at": "2026-08-18 15:41:20.774219+00:00", "lang": "en", "topics": ["machine-learning", "ai-research"], "entities": ["AlphaEvolve", "arXiv", "Duan et al.", "Williams et al.", "Alman et al."], "alternates": {"html": "https://wpnews.pro/news/improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve", "markdown": "https://wpnews.pro/news/improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve.md", "text": "https://wpnews.pro/news/improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve.txt", "jsonld": "https://wpnews.pro/news/improving-matrix-multiplication-exponent-with-optimization-and-alphaevolve.jsonld"}}