155 Epizód

  1. BI 086 Ken Stanley: Open-Endedness

    Közzétéve: 2020. 10. 12.

  2. BI 085 Ida Momennejad: Learning Representations

    Közzétéve: 2020. 09. 30.

  3. BI 084 György Buzsáki and David Poeppel

    Közzétéve: 2020. 09. 15.

  4. BI 083 Jane Wang: Evolving Altruism in AI

    Közzétéve: 2020. 09. 05.

  5. BI 082 Steve Grossberg: Adaptive Resonance Theory

    Közzétéve: 2020. 08. 26.

  6. BI 081 Pieter Roelfsema: Brain-propagation

    Közzétéve: 2020. 08. 16.

  7. BI 080 Daeyeol Lee: Birth of Intelligence

    Közzétéve: 2020. 08. 06.

  8. BI 079 Romain Brette: The Coding Brain Metaphor

    Közzétéve: 2020. 07. 27.

  9. BI 078 David and John Krakauer: Part 2

    Közzétéve: 2020. 07. 17.

  10. BI 077 David and John Krakauer: Part 1

    Közzétéve: 2020. 07. 14.

  11. BI 076 Olaf Sporns: Network Neuroscience

    Közzétéve: 2020. 07. 04.

  12. BI 075 Jim DiCarlo: Reverse Engineering Vision

    Közzétéve: 2020. 06. 24.

  13. BI 074 Ginger Campbell: Are You Sure?

    Közzétéve: 2020. 06. 16.

  14. BI 073 Megan Peters: Consciousness and Metacognition

    Közzétéve: 2020. 06. 10.

  15. BI 072 Mazviita Chirimuuta: Understanding, Prediction, and Reality

    Közzétéve: 2020. 06. 01.

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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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