Peter Norvig, Director of Research at Google, talks about how programming will change as machine learning becomes more prevalent.
Talk Abstract: How will programming change as machine learning becomes more prevalent? For the AlphaGo program, expert programmers implemented the core search algorithm and the pattern generalization algorithm, expert Go players provided their knowledge on what makes a good Go position, and the system learned by observing games played by master players. But the successor program, AlphaZero, was provided only with the rules of the game, no expert Go knowledge, and no sample games; it learned by self-play alone. This talk considers the tools and techniques for developing software in a machine-learning-centric world.
Peter’s bio: Previously he was head of Google’s core search algorithms group, and of NASA Ames’s Computational Sciences Division, making him NASA’s 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. He was co-teacher of an Artificial 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 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.