155 Odcinki

  1. BI 155 Luiz Pessoa: The Entangled Brain

    Opublikowany: 10.12.2022

  2. BI 154 Anne Collins: Learning with Working Memory

    Opublikowany: 29.11.2022

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

    Opublikowany: 18.11.2022

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

    Opublikowany: 8.11.2022

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

    Opublikowany: 30.10.2022

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

    Opublikowany: 15.10.2022

  7. BI 149 William B. Miller: Cell Intelligence

    Opublikowany: 5.10.2022

  8. BI 148 Gaute Einevoll: Brain Simulations

    Opublikowany: 25.09.2022

  9. BI 147 Noah Hutton: In Silico

    Opublikowany: 13.09.2022

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

    Opublikowany: 7.09.2022

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

    Opublikowany: 28.08.2022

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

    Opublikowany: 17.08.2022

  13. BI 143 Rodolphe Sepulchre: Mixed Feedback Control

    Opublikowany: 5.08.2022

  14. BI 142 Cameron Buckner: The New DoGMA

    Opublikowany: 26.07.2022

  15. BI 141 Carina Curto: From Structure to Dynamics

    Opublikowany: 12.07.2022

  16. BI 140 Jeff Schall: Decisions and Eye Movements

    Opublikowany: 30.06.2022

  17. BI 139 Marc Howard: Compressed Time and Memory

    Opublikowany: 20.06.2022

  18. BI 138 Matthew Larkum: The Dendrite Hypothesis

    Opublikowany: 6.06.2022

  19. BI 137 Brian Butterworth: Can Fish Count?

    Opublikowany: 27.05.2022

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

    Opublikowany: 17.05.2022

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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.

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