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Machine Learning Street Talk (MLST)

Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship

Episodes

Total: 221

#60 Geometric Deep Learning Blueprint (Special Edition)
2021/9/19

Patreon: https://www.patreon.com/mlst The last decade has witnessed an experimental revolution in da

#59 - Jeff Hawkins (Thousand Brains Theory)
2021/9/3

Patreon: https://www.patreon.com/mlst The ultimate goal of neuroscience is to learn how the human br

#58 Dr. Ben Goertzel - Artificial General Intelligence
2021/8/11

The field of Artificial Intelligence was founded in the mid 1950s with the aim of constructing “thin

#57 - Prof. Melanie Mitchell - Why AI is harder than we think
2021/7/25

Since its beginning in the 1950s, the field of artificial intelligence has vacillated between period

#56 - Dr. Walid Saba, Gadi Singer, Prof. J. Mark Bishop (Panel discussion)
2021/7/8

It has been over three decades since the statistical revolution overtook AI by a storm and over two

#55 Self-Supervised Vision Models (Dr. Ishan Misra - FAIR).
2021/6/21

Dr. Ishan Misra is a Research Scientist at Facebook AI Research where he works on Computer Vision an

#54 Gary Marcus and Luis Lamb - Neurosymbolic models
2021/6/4

Professor Gary Marcus is a scientist, best-selling author, and entrepreneur. He is Founder and CEO o

#53 Quantum Natural Language Processing - Prof. Bob Coecke (Oxford)
2021/5/19

Bob Coercke is a celebrated physicist, he's been a Physics and Quantum professor at Oxford Universit

#52 - Unadversarial Examples (Hadi Salman, MIT)
2021/5/1

Performing reliably on unseen or shifting data distributions is a difficult challenge for modern vis

#51 Francois Chollet - Intelligence and Generalisation
2021/4/16

In today's show we are joined by Francois Chollet, I have been inspired by Francois ever since I rea

#50 Christian Szegedy - Formal Reasoning, Program Synthesis
2021/4/4

Dr. Christian Szegedy from Google Research is a deep learning heavyweight. He invented adversarial e

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

2021/3/23

The race is on, we are on a collective mission to understand and create artificial general intellige

#48 Machine Learning Security - Andy Smith
2021/3/16

First episode in a series we are doing on ML DevOps. Starting with the thing which nobody seems to b

047 Interpretable Machine Learning - Christoph Molnar
2021/3/14

Christoph Molnar is one of the main people to know in the space of interpretable ML. In 2018 he rele

#046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)
2021/3/6

Academics think of themselves as trailblazers, explorers — seekers of the truth. Any fundamental dis

#045 Microsoft's Platform for Reinforcement Learning (Bonsai)
2021/2/28

Microsoft has an interesting strategy with their new “autonomous systems” technology also known as P

#044 - Data-efficient Image Transformers (Hugo Touvron)
2021/2/25

Today we are going to talk about the *Data-efficient image Transformers paper or (DeiT) which Hugo i

#043 Prof J. Mark Bishop - Artificial Intelligence Is Stupid and Causal Reasoning won't fix it.
2021/2/19

Professor Mark Bishop does not think that computers can be conscious or have phenomenological states

#042 - Pedro Domingos - Ethics and Cancel Culture
2021/2/11

Today we have professor Pedro Domingos and we are going to talk about activism in machine learning,

#041 - Biologically Plausible Neural Networks - Dr. Simon Stringer
2021/2/3

Dr. Simon Stringer. Obtained his Ph.D in mathematical state space control theory and has been a Seni