Brain Inspired

Brain Inspired

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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.

Recent Episodes

  • BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age

    2 weeks ago
  • BI 214 Nicole Rust: How To Actually Fix Brains and Minds

    1 month ago
  • BI 213 Representations in Minds and Brains

    1 month ago
  • BI 212 John Beggs: Why Brains Seek the Edge of Chaos

    2 months ago
  • BI 211 COGITATE: Testing Theories of Consciousness

    2 months ago
  • BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics

    3 months ago
  • BI 209 Aran Nayebi: The NeuroAI Turing Test

    3 months ago
  • BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation

    4 months ago
  • BI 207 Alison Preston: Schemas in our Brains and Minds

    4 months ago
  • Quick Announcement: Complexity Group

    5 months ago