Wednesday / CS Distinguished Lecture

May 14 / 4:00 PM

Hybrid / Mudd 3514

Speaker

Prabhakar Raghavan

Talk Title:

Can AI assist in Mathematics and Computer Science research?

Abstract:

We share our experience using LLMs to obtain new results in mathematics and computer science. We begin with an illustrative example from load-balancing in planet-scale cloud systems, outlining the abilities and limitations of LLMs. Next, we describe our experience with AlphaEvolve, an evolutionary language model from Google DeepMind, to establish new results in the approximability of the Traveling Salesman Problem (TSP), and MAX-CUT problem. We also derive new bounds for several Ramsey numbers. Our methodology entails evolving fleets of Python programs that generate proof chunks to yield these results, and to accelerate proof verification by up to 10,000x. We suggest that our results on inapproximability and Ramsey theory could not have been discovered by hand, and conclude with reflections on the state and promise of AI in mathematics and CS research.

Biography:

Prabhakar Raghavan is the Chief Technologist at Google, where he has held several senior roles since joining in 2012, including Senior Vice President with oversight of Search, Maps, Advertising, Gemini and Payments, and before that, responsibility for Gmail, Google Drive, Calendar and Google Docs. Previously, he led Yahoo! Labs and served as CTO at Verity, Inc following over a decade at IBM Research. He co-authored the textbooks Randomized Algorithms and Introduction to Information Retrieval. Raghavan received a PhD from Berkeley and a Dottore ad honorem from the University of Bologna, and is a member of the National Academy of Engineering.

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Zoom: TBA

Panopto: TBA