Brain Inspired

A podcast by Paul Middlebrooks

Categories:

Education Technology

127 Episodes

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

    Published: 2/10/2022

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

    Published: 1/31/2022

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

    Published: 1/19/2022

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

    Published: 1/5/2022

  5. BI 123 Irina Rish: Continual Learning

    Published: 12/26/2021

  6. BI 122 Kohitij Kar: Visual Intelligence

    Published: 12/12/2021

  7. BI 121 Mac Shine: Systems Neurobiology

    Published: 12/2/2021

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

    Published: 11/21/2021

  9. BI 119 Henry Yin: The Crisis in Neuroscience

    Published: 11/11/2021

  10. BI 118 Johannes Jäger: Beyond Networks

    Published: 11/1/2021

  11. BI 117 Anil Seth: Being You

    Published: 10/19/2021

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

    Published: 10/12/2021

  13. BI 115 Steve Grossberg: Conscious Mind, Resonant Brain

    Published: 10/2/2021

  14. BI 114 Mark Sprevak and Mazviita Chirimuuta: Computation and the Mind

    Published: 9/22/2021

  15. BI 113 David Barack and John Krakauer: Two Views On Cognition

    Published: 9/12/2021

  16. BI ViDA Panel Discussion: Deep RL and Dopamine

    Published: 9/2/2021

  17. BI 112 Ali Mohebi and Ben Engelhard: The Many Faces of Dopamine

    Published: 8/26/2021

  18. BI NMA 06: Advancing Neuro Deep Learning Panel

    Published: 8/19/2021

  19. BI NMA 05: NLP and Generative Models Panel

    Published: 8/13/2021

  20. BI NMA 04: Deep Learning Basics Panel

    Published: 8/6/2021

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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.