World Model · podcast knowledge graph

68 | Melanie Mitchell on Artificial Intelligence and the Challenge of Common Sense

2019-10-14 · 82 min · episode 68 · 8 entities

episode page audio

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    evidence rules-v4
    author of An Introduction to Genetic Algorithms
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    Feed author/publisher: Sean Carroll
  • → discusses Science concept
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    Feed category: Science
  • → discusses Physics concept
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    Feed category: Physics

Entities found in this episode

concepts 4

  • mentioned Science concept
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    evidence rules-v4
    Feed category: Science
  • mentioned Physics concept
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    evidence rules-v4
    Feed category: Physics
  • discusses Science concept
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    evidence rules-v4
    Feed category: Science
  • discusses Physics concept
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    evidence rules-v4
    Feed category: Physics

books 2

persons 2

  • mentioned Sean Carroll person
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    evidence rules-v4
    Feed author/publisher: Sean Carroll
  • hosted by Sean Carroll person
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    evidence rules-v4
    Feed author/publisher: Sean Carroll
Episode description as stored
Artificial intelligence is better than humans at playing chess or go, but still has trouble holding a conversation or driving a car. A simple way to think about the discrepancy is through the lens of "common sense" — there are features of the world, from the fact that tables are solid to the prediction that a tree won't walk across the street, that humans take for granted but that machines have difficulty learning. Melanie Mitchell is a computer scientist and complexity researcher who has written a new book about the prospects of modern AI. We talk about deep learning and other AI strategies, why they currently fall short at equipping computers with a functional "folk physics" understanding of the world, and how we might move forward. Support Mindscape on  Patreon . Melanie Mitchell received her Ph.D. in computer science from the University of Michigan. She is currently a professor of computer science at Portland State University and an external professor at the Santa Fe Institute. Her research focuses on genetic algorithms, cellular automata, and analogical reasoning. She is the author of  An Introduction to Genetic Algorithms, Complexity: A Guided Tour , and most recently  Artificial Intelligence: A Guide for Thinking Humans . She originated the Santa Fe Institute's Complexity Explorer project, on online learning resource for complex systems. Web site Santa Fe web page Wikipedia Google Scholar Complexity Explorer Amazon.com author page Twitter