Machine Learning Street Talk (MLST)
Een podcast door Machine Learning Street Talk (MLST)
217 Afleveringen
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#56 - Dr. Walid Saba, Gadi Singer, Prof. J. Mark Bishop (Panel discussion)
Gepubliceerd: 8-7-2021 -
#55 Self-Supervised Vision Models (Dr. Ishan Misra - FAIR).
Gepubliceerd: 21-6-2021 -
#54 Gary Marcus and Luis Lamb - Neurosymbolic models
Gepubliceerd: 4-6-2021 -
#53 Quantum Natural Language Processing - Prof. Bob Coecke (Oxford)
Gepubliceerd: 19-5-2021 -
#52 - Unadversarial Examples (Hadi Salman, MIT)
Gepubliceerd: 1-5-2021 -
#51 Francois Chollet - Intelligence and Generalisation
Gepubliceerd: 16-4-2021 -
#50 Christian Szegedy - Formal Reasoning, Program Synthesis
Gepubliceerd: 4-4-2021 -
#49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)
Gepubliceerd: 23-3-2021 -
#48 Machine Learning Security - Andy Smith
Gepubliceerd: 16-3-2021 -
047 Interpretable Machine Learning - Christoph Molnar
Gepubliceerd: 14-3-2021 -
#046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)
Gepubliceerd: 6-3-2021 -
#045 Microsoft's Platform for Reinforcement Learning (Bonsai)
Gepubliceerd: 28-2-2021 -
#044 - Data-efficient Image Transformers (Hugo Touvron)
Gepubliceerd: 25-2-2021 -
#043 Prof J. Mark Bishop - Artificial Intelligence Is Stupid and Causal Reasoning won't fix it.
Gepubliceerd: 19-2-2021 -
#042 - Pedro Domingos - Ethics and Cancel Culture
Gepubliceerd: 11-2-2021 -
#041 - Biologically Plausible Neural Networks - Dr. Simon Stringer
Gepubliceerd: 3-2-2021 -
#040 - Adversarial Examples (Dr. Nicholas Carlini, Dr. Wieland Brendel, Florian Tramèr)
Gepubliceerd: 31-1-2021 -
#039 - Lena Voita - NLP
Gepubliceerd: 23-1-2021 -
#038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned
Gepubliceerd: 20-1-2021 -
#037 - Tour De Bayesian with Connor Tann
Gepubliceerd: 11-1-2021
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/).