This Vienna Gödel Lecture provides a fascinating talk by Peter Norvig, Research Director at Google Inc. in the field of intelligent computers. Norvig talks about his long experience in AI and Machine Learning. Computer scientists have developed complex programming languages and systems to allow us to describe, step-by-step how to solve problems such as keeping bank statements balanced. But there are other problems that we can’t articulate how to solve them: how do we recognize a person’s face, or translate a paragraph from German to English? We can’t describe how we do it, and so we can’t easily program a computer to do it, but we can train a computer to learn how to do it. This talk explains how computers learn from examples and what are the promises and limitations of these techniques.
Previously, Norvig was head of Google’s core search algorithms group, and of NASA Ames’s Computational Sciences Division, making him NASA’s most senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has taught at the University of Southern California and the University of California at Berkeley, from which he received a Ph.D. in 1986 and the distinguished alumni award in 2006.
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