Machine Learning Street Talk (MLST)

Podcast készítő Machine Learning Street Talk (MLST)

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216 Epizód

  1. Yoshua Bengio - Designing out Agency for Safe AI

    Közzétéve: 2025. 01. 15.
  2. Francois Chollet - ARC reflections - NeurIPS 2024

    Közzétéve: 2025. 01. 09.
  3. Jeff Clune - Agent AI Needs Darwin

    Közzétéve: 2025. 01. 04.
  4. Neel Nanda - Mechanistic Interpretability (Sparse Autoencoders)

    Közzétéve: 2024. 12. 07.
  5. Jonas Hübotter (ETH) - Test Time Inference

    Közzétéve: 2024. 12. 01.
  6. How AI Could Be A Mathematician's Co-Pilot by 2026 (Prof. Swarat Chaudhuri)

    Közzétéve: 2024. 11. 25.
  7. Nora Belrose - AI Development, Safety, and Meaning

    Közzétéve: 2024. 11. 17.
  8. Why Your GPUs are underutilised for AI - CentML CEO Explains

    Közzétéve: 2024. 11. 13.
  9. Eliezer Yudkowsky and Stephen Wolfram on AI X-risk

    Közzétéve: 2024. 11. 11.
  10. Pattern Recognition vs True Intelligence - Francois Chollet

    Közzétéve: 2024. 11. 06.
  11. The Elegant Math Behind Machine Learning - Anil Ananthaswamy

    Közzétéve: 2024. 11. 04.
  12. Michael Levin - Why Intelligence Isn't Limited To Brains.

    Közzétéve: 2024. 10. 24.
  13. Speechmatics CTO - Next-Generation Speech Recognition

    Közzétéve: 2024. 10. 23.
  14. Dr. Sanjeev Namjoshi - Active Inference

    Közzétéve: 2024. 10. 22.
  15. Joscha Bach - Why Your Thoughts Aren't Yours.

    Közzétéve: 2024. 10. 20.
  16. Decompiling Dreams: A New Approach to ARC? - Alessandro Palmarini

    Közzétéve: 2024. 10. 19.
  17. It's Not About Scale, It's About Abstraction - Francois Chollet

    Közzétéve: 2024. 10. 12.
  18. Bold AI Predictions From Cohere Co-founder

    Közzétéve: 2024. 10. 10.
  19. Open-Ended AI: The Key to Superhuman Intelligence? - Prof. Tim Rocktäschel

    Közzétéve: 2024. 10. 04.
  20. Ben Goertzel on "Superintelligence"

    Közzétéve: 2024. 10. 01.

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Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship show covers current affairs in AI, cognitive science, neuroscience and philosophy of mind with in-depth analysis. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI, and we touch on all of the main ideas in the field with the hype surgically removed. MLST is run by Tim Scarfe, Ph.D (https://www.linkedin.com/in/ecsquizor/) and features regular appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).

Visit the podcast's native language site