165 Episodio

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

    Pubblicato: 28/08/2022

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

    Pubblicato: 17/08/2022

  3. BI 143 Rodolphe Sepulchre: Mixed Feedback Control

    Pubblicato: 05/08/2022

  4. BI 142 Cameron Buckner: The New DoGMA

    Pubblicato: 26/07/2022

  5. BI 141 Carina Curto: From Structure to Dynamics

    Pubblicato: 12/07/2022

  6. BI 140 Jeff Schall: Decisions and Eye Movements

    Pubblicato: 30/06/2022

  7. BI 139 Marc Howard: Compressed Time and Memory

    Pubblicato: 20/06/2022

  8. BI 138 Matthew Larkum: The Dendrite Hypothesis

    Pubblicato: 06/06/2022

  9. BI 137 Brian Butterworth: Can Fish Count?

    Pubblicato: 27/05/2022

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

    Pubblicato: 17/05/2022

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

    Pubblicato: 06/05/2022

  12. BI 134 Mandyam Srinivasan: Bee Flight and Cognition

    Pubblicato: 27/04/2022

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

    Pubblicato: 15/04/2022

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

    Pubblicato: 03/04/2022

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

    Pubblicato: 26/03/2022

  16. BI 130 Eve Marder: Modulation of Networks

    Pubblicato: 13/03/2022

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

    Pubblicato: 02/03/2022

  18. BI 128 Hakwan Lau: In Consciousness We Trust

    Pubblicato: 20/02/2022

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

    Pubblicato: 10/02/2022

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

    Pubblicato: 31/01/2022

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.

Visit the podcast's native language site