As We May Program
Innovations in machine learning are changing our perception of what is possible to do with a computer. But how will machine learning change the way we program, the tools we use, and the mix of tasks done by expert programmers, novice programmers, and non-programmers? This talk examines some possible futures.
发言人详细信息
Peter Norvig is a Director of Research at Google Inc. Previously he was head of Googles core search algorithms group, and of NASA Amess Computational Sciences Division, making him NASAs 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 worlds longest palindromic sentence. He is a fellow of the AAAI, ACM, California Academy of Science and American Academy of Arts and Science.
- 日期:
- 演讲者:
- Peter Norvig
- 所属机构:
系列: MSR AI Distinguished Lectures and Fireside Chats
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Frontiers in Machine Learning: Fireside Chat
Speakers:- Christopher Bishop,
- Peter Lee,
- Sandy Blyth
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Learning over sets, subgraphs, and streams: How to accurately incorporate graph context
Speakers:- Debadeepta Dey,
- Paul Bennett,
- Sean Andrist
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Fireside Chat with Anca Dragan
Speakers:- Anca Dragan and Eric Horvitz
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Conversations Based on Search Engine Result Pages
Speakers:- Maarten de Rijke
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The Ethical Algorithm
Speakers:- Michael Kearns
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Fireside Chat with Stefanie Jegelka
Speakers:- Alekh Agarwal
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Fireside Chat with Peter Stone
Speakers: -
Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation
Speakers:- Debadeepta Dey
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Building Neural Network Models That Can Reason
Speakers:- Christopher Manning
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Fireside Chat with David Blei
Speakers: -
The Blessings of Multiple Causes
Speakers:- David Blei
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As We May Program
Speakers:- Peter Norvig
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Fireside Chat with Peter Norvig
Speakers:- Eric Horvitz,
- Peter Norvig
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An Optimization-Based Theory of Mind for Human-Robot Interaction
Speakers:- Anca Dragan
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Fireside Chat with Manuel Blum
Speakers: -
Towards a Conscious AI: A Computer Architecture inspired by Neuroscience
Speakers:- Adith Swaminathan
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Fireside Chat with Dario Amodei
Speakers: -
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Super-Human AI for Strategic Reasoning
Speakers:- Adith Swaminathan