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    BI 030 Jay McClelland: Mathematical Reasoning and PDP

    BI 030 Jay McClelland: Mathematical Reasoning and PDP

    FromBrain Inspired

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    BI 030 Jay McClelland: Mathematical Reasoning and PDP

    FromBrain Inspired

    ratings:
    Length:
    65 minutes
    Released:
    Mar 27, 2019
    Format:
    Podcast episode

    Description

    Jay's homepage at Stanford.Implementing mathematical reasoning in machines:The video lecture.The paper.Parallel Distributed Processing by Rumelhart and McClelland.Complimentary Learning Systems Theory and Its Recent Update.Episode 28 with Sam Gershman about building machines that learn and think like humans.Check out my interview on Ginger Campbell's Brain Science podcast.
    Released:
    Mar 27, 2019
    Format:
    Podcast episode

    Titles in the series (100)

    Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.