Peter Norvig on writing the field-defining AI textbook, why utility functions are the hard part, and the limits of deep learning.

Peter Norvig — Director of Research at Google and co-author, with Stuart Russell, of 'Artificial Intelligence: A Modern Approach,' the textbook that trained a generation of AI researchers. He also taught one of the first massive open online AI courses.
Lex Fridman interviews Peter Norvig about the evolution of his and Stuart Russell's AI textbook across four editions and how the field shifted from boolean logic and knowledge engineering toward probability and machine learning. Norvig argues the harder problem is no longer optimizing a utility function but deciding what that function should be, raising questions of fairness, bias, and trust. He discusses the brittleness of deep learning and adversarial examples, the value of testing and conversation over simple explanations, and lessons from teaching a 160,000-student MOOC. The conversation closes on programming as problem-solving, the elegance of Lisp, the rise of Python, and his measured view of AI's threats and opportunities.
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Peter Norvig and Stuart Russell
“the co-author with stuart russell of the book artificial intelligence and modern approach that educated and inspired a whole generation of researchers” — Lex Fridman 00:00:00Find it on Amazon
Peter Norvig
“i did my list book in the 90s and one of the things i wanted to do was say uh here's how you do an object system” — Peter Norvig 00:41:46Find it on Amazon