Episode

Google AlphaEvolve - Discovering new science (exclusive interview)

Podcast
Machine Learning Street Talk (MLST)
Published
May 14, 2025
Duration seconds
4438
Processing state
processed
Canonical source
https://podcasters.spotify.com/pod/show/machinelearningstreettalk/episodes/Google-AlphaEvolve---Discovering-new-science-exclusive-interview-e32rjpn
Audio
https://anchor.fm/s/1e4a0eac/podcast/play/102665463/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-4-14%2F400288116-44100-2-bf56074113cbc.mp3
JSON
/v1/public/podcasts/machine-learning-street-talk/episodes/google-alphaevolve-discovering-new-science-exclusive-interview
Markdown
/podcast/machine-learning-street-talk/google-alphaevolve-discovering-new-science-exclusive-interview.md

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Summary

Today GoogleDeepMind released AlphaEvolve: a Gemini coding agent for algorithm discovery. It beat the famous Strassen algorithm for matrix multiplication set 56 years ago. Google has been killing it recently. We had early access to the paper and interviewed the researchers behind the work. AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/ Authors: Alexander Novikov*, Ngân Vũ*, Marvin Eisenberger*, Emilien Dupont*, Po-Sen Huang*, Adam Zsolt Wagner*, Sergey Shirobokov*, Borislav Kozlovskii*, Francisco J. R. Ruiz, Abbas Mehrabian, M. Pawan Kumar, Abigail See, Swarat Chaudhuri, George Holland, Alex Davies, Sebastian Nowozin, Pushmeet Kohli, Matej Balog* (* indicates equal contribution or special designation, if defined elsewhere) SPONSOR MESSAGES: *** Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on o-series style reasoning and AGI. They are hiring a Chief Engineer and ML engineers. Events in Zurich. Goto https://tufalabs.ai/ *** AlphaEvolve works like a very smart, tireless programmer. It uses powerful AI language models (like Gemini) to generate ideas for computer code. Then, it uses an "evolutionary" process – like survival of the fittest for programs. It tries out many different program ideas, automatically tests how well they solve a problem, and then uses the best ones to inspire new, even better programs. Beyond this mathematical breakthrough, AlphaEvolve has already been used to improve real-world systems at Google, such as making their massive data centers run more efficiently and even speeding up the training of the AI models that power AlphaEvolve itself. The discussion…