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Machine Learning Street Talk


This is the audio podcast for the ML Street Talk YouTube channel at Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in theRead more

Popular episodes

061: Interpolation, Extrapolation and Linearisation (Prof. Yann LeCun, Dr. Randall Balestriero)

Jan 4 • 03:19:43

We are now sponsored by Weights and Biases! Please visit our sponsor link:

Siraj Raval - Stories about YouTube, Plagiarism, and the Dangers of Fame (Interview)

Oct 31 • 01:06:44

Yannic has a conversation with Siraj Raval about his journey on YouTube, and the perils of fame....

#60 Geometric Deep Learning Blueprint (Special Edition)

Sep 19 • 03:33:22

The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Many high-dimensional learning tasks previously thought to be beyond reach -- such as computer vision, playing Go, or protein folding -- are in fact tractable given enough computational horsepower. Remarkably, the essence of deep learning is b...

#59 - Jeff Hawkins (Thousand Brains Theory)

Sep 3 • 02:34:51

The ultimate goal of neuroscience is to learn how the human brain gives rise to human intelligence and what it means to be intelligent. Understanding how the brain works is considered one of humanity’s greatest challenges. ...

#58 Dr. Ben Goertzel - Artificial General Intelligence

Aug 11 • 02:28:14

The field of Artificial Intelligence was founded in the mid 1950s with the aim of constructing “thinking machines” - that is to say, computer systems with human-like general intelligence. Think of humanoid robots that not only look but act and think with intelligence equal to and ultimately greater than that of human beings. But in the intervening years, the field has drif...

#57 - Prof. Melanie Mitchell - Why AI is harder than we think

Jul 25 • 02:31:21

Since its beginning in the 1950s, the field of artificial intelligence has vacillated between periods of optimistic predictions and massive investment and periods of disappointment, loss of confidence, and reduced funding. Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots,...

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

Jul 8 • 01:11:17

It has been over three decades since the statistical revolution overtook AI by a storm and over two  decades since deep learning (DL) helped usher the latest resurgence of artificial intelligence (AI). However, the disappointing progress in conversational agents, NLU, and self-driving cars, has made it clear that progress has not lived up to the promise of these empirical ...

#55 Self-Supervised Vision Models (Dr. Ishan Misra - FAIR).

Jun 21 • 01:36:21

Dr. Ishan Misra is a Research Scientist at Facebook AI Research where he works on Computer Vision and Machine Learning. His main research interest is reducing the need for human supervision, and indeed, human knowledge in visual learning systems. He finished his PhD at the Robotics Institute at Carnegie Mellon. He has done stints at Microsoft Research, INRIA and Yale. His ...

#54 Gary Marcus and Luis Lamb - Neurosymbolic models

Jun 4 • 02:24:12

Professor Gary Marcus is a scientist, best-selling author, and entrepreneur. He is Founder and CEO of Robust.AI, and was Founder and CEO of Geometric Intelligence, a machine learning company acquired by Uber in 2016. Gary said in his recent next decade paper that — without us, or other creatures like us, the world would continue to exist, but it would not be described, dis...

#53 Quantum Natural Language Processing - Prof. Bob Coecke (Oxford)

May 19 • 02:17:39

Bob Coercke is a celebrated physicist, he's been a Physics and Quantum professor at Oxford University for the last 20 years. He is particularly interested in Structure which is to say, Logic, Order, and Category Theory. He is well known for work involving compositional distributional models of natural language meaning and he is also fascinated with understanding how our br...

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