CS&E Seminar: Jeff Dean - Modern Advances in Machine Learning

Event Details

Jeff Dean - Chief Scientist, Google Research and Google DeepMind
Title: Modern Advances in Machine Learning and What Will They Enable?

Wednesday, May 14
10:30 a.m. - 12 p.m.
3-180 Keller Hall

Schedule

10:30 - 11 a.m. | Pre-lecture reception (lobby outside of 3-180)
11 a.m. - 12 p.m. | Seminar (3-180)

Abstract

In this talk I'll highlight some of the research and computer systems advances that have come together to create the capabilities of modern AI models.  I'll discuss the Gemini family of models and discuss the research advances that these models are built on, and highlight some of the uses enabled by aspects like multimodality, long-context and in-context learning, and inference time computation to enable more sophisticated reasoning.  With powerful capabilities and continuing rapid advances, modern AI has the potential to reshape much of what we do.  I'll discuss some potential areas that may be radically shaped by AI developments, and how collaboration between AI researchers and practitioners, policymakers, and other stakeholders can maximize the upsides of AI and minimize its downsides.

This talk will present work done by many people at Google.

Biography

Jeff Dean joined Google in 1999 where he now serves as Google’s Chief Scientist, focusing on AI advances for Google DeepMind and Google Research. He is a co-lead of the Gemini project, and his areas of focus include machine learning and AI, and applications of AI to problems that help billions of people in societally beneficial ways. His work has been integral to many generations of Google’s search engine, its initial ad serving system, distributed computing infrastructure such as BigTable and MapReduce, Google's TPU machine learning hardware, the Tensorflow open-source machine learning system, and Gemini multimodal models, among many other things.

Jeff received a Ph.D. in Computer Science from the University of Washington and a B.S. in Computer Science & Economics from the University of Minnesota, summa cum laude.  He is a member of the U.S. National Academy of Engineering and of the American Academy of Arts and Sciences, and a Fellow of the Association for Computing Machinery (ACM) , and a winner of the 2012 ACM Prize in Computing and the 2021 IEEE John von Neumann medal.