155 Episodes

  1. BI 102 Mark Humphries: What Is It Like To Be A Spike?

    Published: 4/16/2021

  2. BI 101 Steve Potter: Motivating Brains In and Out of Dishes

    Published: 4/6/2021

  3. BI 100.6 Special: Do We Have the Right Vocabulary and Concepts?

    Published: 3/28/2021

  4. BI 100.4 Special: What Ideas Are Holding Us Back?

    Published: 3/21/2021

  5. BI 100.3 Special: Can We Scale Up to AGI with Current Tech?

    Published: 3/17/2021

  6. BI 100.2 Special: What Are the Biggest Challenges and Disagreements?

    Published: 3/12/2021

  7. BI 100.1 Special: What Has Improved Your Career or Well-being?

    Published: 3/9/2021

  8. BI 099 Hakwan Lau and Steve Fleming: Neuro-AI Consciousness

    Published: 2/28/2021

  9. BI 098 Brian Christian: The Alignment Problem

    Published: 2/18/2021

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

    Published: 2/8/2021

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

    Published: 1/29/2021

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

    Published: 1/19/2021

  13. BI 094 Alison Gopnik: Child-Inspired AI

    Published: 1/8/2021

  14. BI 093 Dileep George: Inference in Brain Microcircuits

    Published: 12/29/2020

  15. BI 092 Russ Poldrack: Cognitive Ontologies

    Published: 12/15/2020

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

    Published: 12/4/2020

  17. BI 090 Chris Eliasmith: Building the Human Brain

    Published: 11/23/2020

  18. BI 089 Matt Smith: Drifting Cognition

    Published: 11/12/2020

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

    Published: 11/2/2020

  20. BI 087 Dileep George: Cloning for Cognitive Maps

    Published: 10/23/2020

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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.