155 Episodes

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

    Published: 5/6/2022

  2. BI 134 Mandyam Srinivasan: Bee Flight and Cognition

    Published: 4/27/2022

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

    Published: 4/15/2022

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

    Published: 4/3/2022

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

    Published: 3/26/2022

  6. BI 130 Eve Marder: Modulation of Networks

    Published: 3/13/2022

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

    Published: 3/2/2022

  8. BI 128 Hakwan Lau: In Consciousness We Trust

    Published: 2/20/2022

  9. BI 127 Tomás Ryan: Memory, Instinct, and Forgetting

    Published: 2/10/2022

  10. BI 126 Randy Gallistel: Where Is the Engram?

    Published: 1/31/2022

  11. BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys

    Published: 1/19/2022

  12. BI 124 Peter Robin Hiesinger: The Self-Assembling Brain

    Published: 1/5/2022

  13. BI 123 Irina Rish: Continual Learning

    Published: 12/26/2021

  14. BI 122 Kohitij Kar: Visual Intelligence

    Published: 12/12/2021

  15. BI 121 Mac Shine: Systems Neurobiology

    Published: 12/2/2021

  16. BI 120 James Fitzgerald, Andrew Saxe, Weinan Sun: Optimizing Memories

    Published: 11/21/2021

  17. BI 119 Henry Yin: The Crisis in Neuroscience

    Published: 11/11/2021

  18. BI 118 Johannes Jäger: Beyond Networks

    Published: 11/1/2021

  19. BI 117 Anil Seth: Being You

    Published: 10/19/2021

  20. BI 116 Michael W. Cole: Empirical Neural Networks

    Published: 10/12/2021

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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.