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Peter Norvig | Stanford HAI

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peopleDistinguished Fellows

Peter Norvig

Distinguished Education Fellow, Stanford HAI

External Bio

Peter Norvig is a Distinguished Education Fellow at Stanford's Human-Centered Artificial Intelligence Institute and a researcher at Google Inc; previously he directed Google's core search algorithms group and Google's Research group. He was head of NASA Ames's Computational Sciences Division, where he was NASA's senior computer scientist and a recipient of NASA's Exceptional Achievement Award in 2001. He has taught at the University of Southern California, Stanford University, and the University of California at Berkeley, from which he received a Ph.D. in 1986 and the distinguished alumni award in 2006. He was co-teacher of an Artifical Intelligence class that signed up 160,000 students, helping to kick off the current round of massive open online classes. His publications include the books Data Science in Context (to appear in 2022), Artificial Intelligence: A Modern Approach (the leading textbook in the field), Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX. He is also the author of the Gettysburg Powerpoint Presentation and the world's longest palindromic sentence. He is a fellow of the AAAI, ACM, California Academy of Science and American Academy of Arts & Sciences.

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Latest Related to Peter Norvig

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OpenAI Fast-Tracks AI Agents. How Do We Balance Benefits With Risks?

Forbes
Oct 04

Peter Norvig, Distinguished Education Fellow at the Stanford HAI, comments on how limiting the budget at an AI agent’s disposal as well as transaction times and capabilities can help AI agents “operate safely within defined boundaries."

Research

Generative AI: Perspectives from Stanford HAI

Peter Norvig, Erik Brynjolfsson, James Landay, Michele Elam, Daniel E. Ho, Rob Reich, Surya Ganguli, Christopher Manning, Curtis Langlotz, Vanessa Parli, Percy Liang, Fei-Fei Li, Russ Altman
Generative AIDeep DiveMar 01

A diversity of perspectives from Stanford leaders in medicine, science, engineering, humanities, and the social sciences on how generative AI might affect their fields and our world