167 Odcinki

  1. BI 147 Noah Hutton: In Silico

    Opublikowany: 13.09.2022

  2. BI 146 Lauren Ross: Causal and Non-Causal Explanation

    Opublikowany: 7.09.2022

  3. BI 145 James Woodward: Causation with a Human Face

    Opublikowany: 28.08.2022

  4. BI 144 Emily M. Bender and Ev Fedorenko: Large Language Models

    Opublikowany: 17.08.2022

  5. BI 143 Rodolphe Sepulchre: Mixed Feedback Control

    Opublikowany: 5.08.2022

  6. BI 142 Cameron Buckner: The New DoGMA

    Opublikowany: 26.07.2022

  7. BI 141 Carina Curto: From Structure to Dynamics

    Opublikowany: 12.07.2022

  8. BI 140 Jeff Schall: Decisions and Eye Movements

    Opublikowany: 30.06.2022

  9. BI 139 Marc Howard: Compressed Time and Memory

    Opublikowany: 20.06.2022

  10. BI 138 Matthew Larkum: The Dendrite Hypothesis

    Opublikowany: 6.06.2022

  11. BI 137 Brian Butterworth: Can Fish Count?

    Opublikowany: 27.05.2022

  12. BI 136 Michel Bitbol and Alex Gomez-Marin: Phenomenology

    Opublikowany: 17.05.2022

  13. BI 135 Elena Galea: The Stars of the Brain

    Opublikowany: 6.05.2022

  14. BI 134 Mandyam Srinivasan: Bee Flight and Cognition

    Opublikowany: 27.04.2022

  15. BI 133 Ken Paller: Lucid Dreaming, Memory, and Sleep

    Opublikowany: 15.04.2022

  16. BI 132 Ila Fiete: A Grid Scaffold for Memory

    Opublikowany: 3.04.2022

  17. BI 131 Sri Ramaswamy and Jie Mei: Neuromodulation-aware DNNs

    Opublikowany: 26.03.2022

  18. BI 130 Eve Marder: Modulation of Networks

    Opublikowany: 13.03.2022

  19. BI 129 Patryk Laurent: Learning from the Real World

    Opublikowany: 2.03.2022

  20. BI 128 Hakwan Lau: In Consciousness We Trust

    Opublikowany: 20.02.2022

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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.

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