Mathematics and Physics have had extraordinary success in modeling the physical world. We have no trouble calculating exactly when the next solar eclipse will occur. But in has proven much harder to create mathematical models of how people will act. There are no simple formulas like “F = m a” to describe the actions of people. However, computer models based on aggregating and summarizing large amounts of data have proven to be very effective at a large number of tasks. This talk gives some examples in understanding speech, language translation, and recognizing objects in images and videos.
Peter Norvig is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. At Google Inc he was Director of Search Quality, responsible for the core web search algorithms from 2002-2005, and has been Director of Research from 2005 on.
Previously he was the head of the Computational Sciences Division at NASA Ames Research Center, making him NASA’s senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has served as an assistant professor at the University of Southern California and a research faculty member at the University of California at Berkeley Computer Science Department, from which he received a Ph.D. in 1986 and the distinguished alumni award in 2006. He has over fifty publications in Computer Science, concentrating on Artificial Intelligence, Natural Language Processing and Software Engineering, including the books 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.