167 Avsnitt

  1. BI 147 Noah Hutton: In Silico

    Publicerades: 2022-09-13

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

    Publicerades: 2022-09-07

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

    Publicerades: 2022-08-28

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

    Publicerades: 2022-08-17

  5. BI 143 Rodolphe Sepulchre: Mixed Feedback Control

    Publicerades: 2022-08-05

  6. BI 142 Cameron Buckner: The New DoGMA

    Publicerades: 2022-07-26

  7. BI 141 Carina Curto: From Structure to Dynamics

    Publicerades: 2022-07-12

  8. BI 140 Jeff Schall: Decisions and Eye Movements

    Publicerades: 2022-06-30

  9. BI 139 Marc Howard: Compressed Time and Memory

    Publicerades: 2022-06-20

  10. BI 138 Matthew Larkum: The Dendrite Hypothesis

    Publicerades: 2022-06-06

  11. BI 137 Brian Butterworth: Can Fish Count?

    Publicerades: 2022-05-27

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

    Publicerades: 2022-05-17

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

    Publicerades: 2022-05-06

  14. BI 134 Mandyam Srinivasan: Bee Flight and Cognition

    Publicerades: 2022-04-27

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

    Publicerades: 2022-04-15

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

    Publicerades: 2022-04-03

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

    Publicerades: 2022-03-26

  18. BI 130 Eve Marder: Modulation of Networks

    Publicerades: 2022-03-13

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

    Publicerades: 2022-03-02

  20. BI 128 Hakwan Lau: In Consciousness We Trust

    Publicerades: 2022-02-20

5 / 9

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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