Peter Norvig from Google: “The Challenges of Creating Software with Machine Learning”

Traditionally, software is built by programmers who consider all the possible situations and write rules to deal with them. But lately, many applications are created by machine learning: the programmer is replaced by a trainer, who shows the computer examples until it learns to complete the task. This shift in the way software is built is opening up exciting new possibilities and posing new challenges.

Peter Norvig is a director of research at Google Inc. 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 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 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 (Association for the Advancement of Artificial Intelligence), ACM (Association for Computing Machinery), California Academy of Science and American Academy of Arts & Sciences.