Machine Learning Street Talk (MLST)

A podcast by Machine Learning Street Talk (MLST)

Categorie:

Tecnica

207 Episodio

  1. Transformers Need Glasses! - Federico Barbero

    Pubblicato: 08/03/2025

  2. Sakana AI - Chris Lu, Robert Tjarko Lange, Cong Lu

    Pubblicato: 01/03/2025

  3. Clement Bonnet - Can Latent Program Networks Solve Abstract Reasoning?

    Pubblicato: 19/02/2025

  4. Prof. Jakob Foerster - ImageNet Moment for Reinforcement Learning?

    Pubblicato: 18/02/2025

  5. Daniel Franzen & Jan Disselhoff - ARC Prize 2024 winners

    Pubblicato: 12/02/2025

  6. Sepp Hochreiter - LSTM: The Comeback Story?

    Pubblicato: 12/02/2025

  7. Want to Understand Neural Networks? Think Elastic Origami! - Prof. Randall Balestriero

    Pubblicato: 08/02/2025

  8. Nicholas Carlini (Google DeepMind)

    Pubblicato: 25/01/2025

  9. Subbarao Kambhampati - Do o1 models search?

    Pubblicato: 23/01/2025

  10. How Do AI Models Actually Think? - Laura Ruis

    Pubblicato: 20/01/2025

  11. Jurgen Schmidhuber on Humans co-existing with AIs

    Pubblicato: 16/01/2025

  12. Yoshua Bengio - Designing out Agency for Safe AI

    Pubblicato: 15/01/2025

  13. Francois Chollet - ARC reflections - NeurIPS 2024

    Pubblicato: 09/01/2025

  14. Jeff Clune - Agent AI Needs Darwin

    Pubblicato: 04/01/2025

  15. Neel Nanda - Mechanistic Interpretability (Sparse Autoencoders)

    Pubblicato: 07/12/2024

  16. Jonas Hübotter (ETH) - Test Time Inference

    Pubblicato: 01/12/2024

  17. How AI Could Be A Mathematician's Co-Pilot by 2026 (Prof. Swarat Chaudhuri)

    Pubblicato: 25/11/2024

  18. Nora Belrose - AI Development, Safety, and Meaning

    Pubblicato: 17/11/2024

  19. Why Your GPUs are underutilised for AI - CentML CEO Explains

    Pubblicato: 13/11/2024

  20. Eliezer Yudkowsky and Stephen Wolfram on AI X-risk

    Pubblicato: 11/11/2024

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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