Machine Learning Street Talk (MLST)

Podcast készítő Machine Learning Street Talk (MLST)

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217 Epizód

  1. #56 - Dr. Walid Saba, Gadi Singer, Prof. J. Mark Bishop (Panel discussion)

    Közzétéve: 2021. 07. 08.
  2. #55 Self-Supervised Vision Models (Dr. Ishan Misra - FAIR).

    Közzétéve: 2021. 06. 21.
  3. #54 Gary Marcus and Luis Lamb - Neurosymbolic models

    Közzétéve: 2021. 06. 04.
  4. #53 Quantum Natural Language Processing - Prof. Bob Coecke (Oxford)

    Közzétéve: 2021. 05. 19.
  5. #52 - Unadversarial Examples (Hadi Salman, MIT)

    Közzétéve: 2021. 05. 01.
  6. #51 Francois Chollet - Intelligence and Generalisation

    Közzétéve: 2021. 04. 16.
  7. #50 Christian Szegedy - Formal Reasoning, Program Synthesis

    Közzétéve: 2021. 04. 04.
  8. #49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)

    Közzétéve: 2021. 03. 23.
  9. #48 Machine Learning Security - Andy Smith

    Közzétéve: 2021. 03. 16.
  10. 047 Interpretable Machine Learning - Christoph Molnar

    Közzétéve: 2021. 03. 14.
  11. #046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)

    Közzétéve: 2021. 03. 06.
  12. #045 Microsoft's Platform for Reinforcement Learning (Bonsai)

    Közzétéve: 2021. 02. 28.
  13. #044 - Data-efficient Image Transformers (Hugo Touvron)

    Közzétéve: 2021. 02. 25.
  14. #043 Prof J. Mark Bishop - Artificial Intelligence Is Stupid and Causal Reasoning won't fix it.

    Közzétéve: 2021. 02. 19.
  15. #042 - Pedro Domingos - Ethics and Cancel Culture

    Közzétéve: 2021. 02. 11.
  16. #041 - Biologically Plausible Neural Networks - Dr. Simon Stringer

    Közzétéve: 2021. 02. 03.
  17. #040 - Adversarial Examples (Dr. Nicholas Carlini, Dr. Wieland Brendel, Florian Tramèr)

    Közzétéve: 2021. 01. 31.
  18. #039 - Lena Voita - NLP

    Közzétéve: 2021. 01. 23.
  19. #038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned

    Közzétéve: 2021. 01. 20.
  20. #037 - Tour De Bayesian with Connor Tann

    Közzétéve: 2021. 01. 11.

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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