155 Episodes

  1. BI 155 Luiz Pessoa: The Entangled Brain

    Published: 12/10/2022

  2. BI 154 Anne Collins: Learning with Working Memory

    Published: 11/29/2022

  3. BI 153 Carolyn Dicey-Jennings: Attention and the Self

    Published: 11/18/2022

  4. BI 152 Michael L. Anderson: After Phrenology: Neural Reuse

    Published: 11/8/2022

  5. BI 151 Steve Byrnes: Brain-like AGI Safety

    Published: 10/30/2022

  6. BI 150 Dan Nicholson: Machines, Organisms, Processes

    Published: 10/15/2022

  7. BI 149 William B. Miller: Cell Intelligence

    Published: 10/5/2022

  8. BI 148 Gaute Einevoll: Brain Simulations

    Published: 9/25/2022

  9. BI 147 Noah Hutton: In Silico

    Published: 9/13/2022

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

    Published: 9/7/2022

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

    Published: 8/28/2022

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

    Published: 8/17/2022

  13. BI 143 Rodolphe Sepulchre: Mixed Feedback Control

    Published: 8/5/2022

  14. BI 142 Cameron Buckner: The New DoGMA

    Published: 7/26/2022

  15. BI 141 Carina Curto: From Structure to Dynamics

    Published: 7/12/2022

  16. BI 140 Jeff Schall: Decisions and Eye Movements

    Published: 6/30/2022

  17. BI 139 Marc Howard: Compressed Time and Memory

    Published: 6/20/2022

  18. BI 138 Matthew Larkum: The Dendrite Hypothesis

    Published: 6/6/2022

  19. BI 137 Brian Butterworth: Can Fish Count?

    Published: 5/27/2022

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

    Published: 5/17/2022

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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.