Machine Learning Street Talk (MLST)

233 Episodes

1. #52 - Unadversarial Examples (Hadi Salman, MIT)

   Published: 5/1/2021
2. #51 Francois Chollet - Intelligence and Generalisation

   Published: 4/16/2021
3. #50 Christian Szegedy - Formal Reasoning, Program Synthesis

   Published: 4/4/2021
4. #49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)

   Published: 3/23/2021
5. #48 Machine Learning Security - Andy Smith

   Published: 3/16/2021
6. 047 Interpretable Machine Learning - Christoph Molnar

   Published: 3/14/2021
7. #046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)

   Published: 3/6/2021
8. #045 Microsoft's Platform for Reinforcement Learning (Bonsai)

   Published: 2/28/2021
9. #044 - Data-efficient Image Transformers (Hugo Touvron)

   Published: 2/25/2021
10. #043 Prof J. Mark Bishop - Artificial Intelligence Is Stupid and Causal Reasoning won't fix it.

    Published: 2/19/2021
11. #042 - Pedro Domingos - Ethics and Cancel Culture

    Published: 2/11/2021
12. #041 - Biologically Plausible Neural Networks - Dr. Simon Stringer

    Published: 2/3/2021
13. #040 - Adversarial Examples (Dr. Nicholas Carlini, Dr. Wieland Brendel, Florian Tramèr)

    Published: 1/31/2021
14. #039 - Lena Voita - NLP

    Published: 1/23/2021
15. #038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned

    Published: 1/20/2021
16. #037 - Tour De Bayesian with Connor Tann

    Published: 1/11/2021
17. #036 - Max Welling: Quantum, Manifolds & Symmetries in ML

    Published: 1/3/2021
18. #035 Christmas Community Edition!

    Published: 12/27/2020
19. #034 Eray Özkural- AGI, Simulations & Safety

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

    Published: 12/13/2020