167 Avsnitt

  1. BI 098 Brian Christian: The Alignment Problem

    Publicerades: 2021-02-18

  2. BI 097 Omri Barak and David Sussillo: Dynamics and Structure

    Publicerades: 2021-02-08

  3. BI 096 Keisuke Fukuda and Josh Cosman: Forking Paths

    Publicerades: 2021-01-29

  4. BI 095 Chris Summerfield and Sam Gershman: Neuro for AI?

    Publicerades: 2021-01-19

  5. BI 094 Alison Gopnik: Child-Inspired AI

    Publicerades: 2021-01-08

  6. BI 093 Dileep George: Inference in Brain Microcircuits

    Publicerades: 2020-12-29

  7. BI 092 Russ Poldrack: Cognitive Ontologies

    Publicerades: 2020-12-15

  8. BI 091 Carsen Stringer: Understanding 40,000 Neurons

    Publicerades: 2020-12-04

  9. BI 090 Chris Eliasmith: Building the Human Brain

    Publicerades: 2020-11-23

  10. BI 089 Matt Smith: Drifting Cognition

    Publicerades: 2020-11-12

  11. BI 088 Randy O’Reilly: Simulating the Human Brain

    Publicerades: 2020-11-02

  12. BI 087 Dileep George: Cloning for Cognitive Maps

    Publicerades: 2020-10-23

  13. BI 086 Ken Stanley: Open-Endedness

    Publicerades: 2020-10-12

  14. BI 085 Ida Momennejad: Learning Representations

    Publicerades: 2020-09-30

  15. BI 084 György Buzsáki and David Poeppel

    Publicerades: 2020-09-15

  16. BI 083 Jane Wang: Evolving Altruism in AI

    Publicerades: 2020-09-05

  17. BI 082 Steve Grossberg: Adaptive Resonance Theory

    Publicerades: 2020-08-26

  18. BI 081 Pieter Roelfsema: Brain-propagation

    Publicerades: 2020-08-16

  19. BI 080 Daeyeol Lee: Birth of Intelligence

    Publicerades: 2020-08-06

  20. BI 079 Romain Brette: The Coding Brain Metaphor

    Publicerades: 2020-07-27

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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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