Machine Learning Street Talk (MLST)

A podcast by Machine Learning Street Talk (MLST)

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190 Episodio

  1. #49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)

    Pubblicato: 23/03/2021
  2. #48 Machine Learning Security - Andy Smith

    Pubblicato: 16/03/2021
  3. 047 Interpretable Machine Learning - Christoph Molnar

    Pubblicato: 14/03/2021
  4. #046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)

    Pubblicato: 06/03/2021
  5. #045 Microsoft's Platform for Reinforcement Learning (Bonsai)

    Pubblicato: 28/02/2021
  6. #044 - Data-efficient Image Transformers (Hugo Touvron)

    Pubblicato: 25/02/2021
  7. #043 Prof J. Mark Bishop - Artificial Intelligence Is Stupid and Causal Reasoning won't fix it.

    Pubblicato: 19/02/2021
  8. #042 - Pedro Domingos - Ethics and Cancel Culture

    Pubblicato: 11/02/2021
  9. #041 - Biologically Plausible Neural Networks - Dr. Simon Stringer

    Pubblicato: 03/02/2021
  10. #040 - Adversarial Examples (Dr. Nicholas Carlini, Dr. Wieland Brendel, Florian Tramèr)

    Pubblicato: 31/01/2021
  11. #039 - Lena Voita - NLP

    Pubblicato: 23/01/2021
  12. #038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned

    Pubblicato: 20/01/2021
  13. #037 - Tour De Bayesian with Connor Tann

    Pubblicato: 11/01/2021
  14. #036 - Max Welling: Quantum, Manifolds & Symmetries in ML

    Pubblicato: 03/01/2021
  15. #035 Christmas Community Edition!

    Pubblicato: 27/12/2020
  16. #034 Eray Özkural- AGI, Simulations & Safety

    Pubblicato: 20/12/2020
  17. #033 Prof. Karl Friston - The Free Energy Principle

    Pubblicato: 13/12/2020
  18. #032- Simon Kornblith / GoogleAI - SimCLR and Paper Haul!

    Pubblicato: 06/12/2020
  19. #031 WE GOT ACCESS TO GPT-3! (With Gary Marcus, Walid Saba and Connor Leahy)

    Pubblicato: 28/11/2020
  20. #030 Multi-Armed Bandits and Pure-Exploration (Wouter M. Koolen)

    Pubblicato: 20/11/2020

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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/).

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