167 Odcinki

  1. Quick Announcement: Complexity Group

    Opublikowany: 5.03.2025

  2. BI 206 Ciara Greene: Memories Are Useful, Not Accurate

    Opublikowany: 26.02.2025

  3. BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think

    Opublikowany: 12.02.2025

  4. BI 204 David Robbe: Your Brain Doesn’t Measure Time

    Opublikowany: 29.01.2025

  5. BI 203 David Krakauer: How To Think Like a Complexity Scientist

    Opublikowany: 14.01.2025

  6. BI 202 Eli Sennesh: Divide-and-Conquer to Predict

    Opublikowany: 3.01.2025

  7. BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors

    Opublikowany: 18.12.2024

  8. BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI

    Opublikowany: 4.12.2024

  9. BI 199 Hessam Akhlaghpour: Natural Universal Computation

    Opublikowany: 26.11.2024

  10. BI 198 Tony Zador: Neuroscience Principles to Improve AI

    Opublikowany: 11.11.2024

  11. BI 197 Karen Adolph: How Babies Learn to Move and Think

    Opublikowany: 25.10.2024

  12. BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød

    Opublikowany: 11.10.2024

  13. BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød

    Opublikowany: 8.10.2024

  14. BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting

    Opublikowany: 27.09.2024

  15. BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI

    Opublikowany: 11.09.2024

  16. BI 192 Àlex Gómez-Marín: The Edges of Consciousness

    Opublikowany: 28.08.2024

  17. BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence

    Opublikowany: 15.08.2024

  18. BI 190 Luis Favela: The Ecological Brain

    Opublikowany: 31.07.2024

  19. BI 189 Joshua Vogelstein: Connectomes and Prospective Learning

    Opublikowany: 29.06.2024

  20. BI 188 Jolande Fooken: Coordinating Action and Perception

    Opublikowany: 27.05.2024

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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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