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PODCAST

Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

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

technology

All Episodes

01:43:54

#107 - Dr. RAPHAËL MILLIÈRE - Linguistics, Theory of...

Machine Learning Street Talk (MLST) ·

2023/03/13

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 Dr. Raphaël Millière is the 2020 Robert A. Burt Presidential Scholar in Society and Neuroscience in the Center for Science and Society, and a Lecturer in the Philosophy Department at Columbia University. His research draws from his expertise in philosophy and cognitive science to explore the implications of recent progress in deep learning for models of human cognition, as well as various issues in ethics and

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02:59:20

#106 - Prof. KARL FRISTON 3.0 - Collective...

Machine Learning Street Talk (MLST) ·

2023/03/11

This show is sponsored by Numerai, please visit them here with our sponsor link (we would really appreciate it) http://numer.ai/mlst Prof. Karl Friston recently proposed a vision of artificial intelligence that goes beyond machines and algorithms, and embraces humans and nature as part of a cyber-physical ecosystem of intelligence. This vision is based on the principle of active inference, which states that intelligent systems can learn from their observations and act on their environment to reduce

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01:20:42

#105 - Dr. MICHAEL OLIVER [CSO - Numerai]

Machine Learning Street Talk (MLST) ·

2023/03/04

Access Numerai here: http://numer.ai/mlst Michael Oliver is the Chief Scientist at Numerai, a hedge fund that crowdsources machine learning models from data scientists. He has a PhD in Computational Neuroscience from UC Berkeley and was a postdoctoral researcher at the Allen Institute for Brain Science before joining Numerai in 2020. He is also the host of Numerai Quant Club, a YouTube series where he discusses Numerai’s research, data and challenges. YT version:

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01:28:54

#104 - Prof. CHRIS SUMMERFIELD - Natural General...

Machine Learning Street Talk (MLST) ·

2023/02/22

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 Christopher Summerfield, Department of Experimental Psychology, University of Oxford is a Professor of Cognitive Neuroscience at the University of Oxford and a Research Scientist at Deepmind UK. His work focusses on the neural and computational mechanisms by which humans make decisions. Chris has just released an incredible new book on AI called "Natural General Intelligence". It's my favourite book on AI I have

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01:01:46

#103 - Prof. Edward Grefenstette - Language,...

Machine Learning Street Talk (MLST) ·

2023/02/11

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT: https://youtu.be/i9VPPmQn9HQ Edward Grefenstette is a Franco-American computer scientist who currently serves as Head of Machine Learning at Cohere and Honorary Professor at UCL. He has previously been a research scientist at Facebook AI Research and staff research scientist at DeepMind, and was also the CTO of Dark Blue Labs. Prior to his move to industry, Edward was a Fulford Junior Research Fellow at

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00:55:17

#102 - Prof. MICHAEL LEVIN, Prof. IRINA RISH -...

Machine Learning Street Talk (MLST) ·

2023/02/11

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT: https://youtu.be/Vbi288CKgis Michael Levin is a Distinguished Professor in the Biology department at Tufts University, and the holder of the Vannevar Bush endowed Chair. He is the Director of the Allen Discovery Center at Tufts and the Tufts Center for Regenerative and Developmental Biology. His research focuses on understanding the biophysical mechanisms of pattern regulation and harnessing endogenous

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00:26:28

#100 Dr. PATRICK LEWIS (co:here) - Retrieval...

Machine Learning Street Talk (MLST) ·

2023/02/10

Dr. Patrick Lewis is a London-based AI and Natural Language Processing Research Scientist, working at co:here. Prior to this, Patrick worked as a research scientist at the Fundamental AI Research Lab (FAIR) at Meta AI. During his PhD, Patrick split his time between FAIR and University College London, working with Sebastian Riedel and Pontus Stenetorp. Patrick’s research focuses on the intersection of information retrieval techniques (IR) and large language models (LLMs). He has done extensive work

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01:39:45

#99 - CARLA CREMER & IGOR KRAWCZUK - X-Risk,...

Machine Learning Street Talk (MLST) ·

2023/02/05

YT version (with references): https://www.youtube.com/watch?v=lxaTinmKxs0 Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 Carla Cremer and Igor Krawczuk argue that AI risk should be understood as an old problem of politics, power and control with known solutions, and that threat models should be driven by empirical work. The interaction between FTX and the Effective Altruism community has sparked a lot of discussion about the dangers of optimization, and Carla's

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01:06:12

[NO MUSIC] #98 - Prof. LUCIANO FLORIDI - ChatGPT,...

Machine Learning Street Talk (MLST) ·

2023/02/03

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT version: https://youtu.be/YLNGvvgq3eg We are living in an age of rapid technological advancement, and with this growth comes a digital divide. Professor Luciano Floridi of the Oxford Internet Institute / Oxford University believes that this divide not only affects our understanding of the implications of this new age, but also the organization of a fair society. The Information Revolution has been transforming

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01:06:51

#98 - Prof. LUCIANO FLORIDI - ChatGPT,...

Machine Learning Street Talk (MLST) ·

2023/02/03

Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 YT version: https://youtu.be/YLNGvvgq3eg (If music annoying, skip to main interview @ 14:14) We are living in an age of rapid technological advancement, and with this growth comes a digital divide. Professor Luciano Floridi of the Oxford Internet Institute / Oxford University believes that this divide not only affects our understanding of the implications of this new age, but also the organization of a fair

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00:24:58

#97 SREEJAN KUMAR - Human Inductive Biases in...

Machine Learning Street Talk (MLST) ·

2023/01/28

Research has shown that humans possess strong inductive biases which enable them to quickly learn and generalize. In order to instill these same useful human inductive biases into machines, a paper was presented by Sreejan Kumar at the NeurIPS conference which won the Outstanding Paper of the Year award. The paper is called Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. This paper focuses on using a controlled stimulus space of two-dimensional binary

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02:49:14

#96 Prof. PEDRO DOMINGOS - There are no infinities,...

Machine Learning Street Talk (MLST) ·

2022/12/30

Pedro Domingos, Professor Emeritus of Computer Science and Engineering at the University of Washington, is renowned for his research in machine learning, particularly for his work on Markov logic networks that allow for uncertain inference. He is also the author of the acclaimed book "The Master Algorithm". Panel: Dr. Tim Scarfe TOC: [00:00:00] Introduction [00:01:34] Galaxtica / misinformation / gatekeeping [00:12:31] Is there a master algorithm? [00:16:29] Limits of our understanding [00:21:57]

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00:39:12

#95 - Prof. IRINA RISH - AGI, Complex Systems,...

Machine Learning Street Talk (MLST) ·

2022/12/26

Canadian Excellence Research Chair in Autonomous AI. Irina holds an MSc and PhD in AI from the University of California, Irvine as well as an MSc in Applied Mathematics from the Moscow Gubkin Institute. Her research focuses on machine learning, neural data analysis, and neuroscience-inspired AI. In particular, she is exploring continual lifelong learning, optimization algorithms for deep neural networks, sparse modelling and probabilistic inference, dialog generation, biologically plausible

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00:13:34

#94 - ALAN CHAN - AI Alignment and Governance #NEURIPS

Machine Learning Street Talk (MLST) ·

2022/12/26

Support us! https://www.patreon.com/mlst Alan Chan is a PhD student at Mila, the Montreal Institute for Learning Algorithms, supervised by Nicolas Le Roux. Before joining Mila, Alan was a Masters student at the Alberta Machine Intelligence Institute and the University of Alberta, where he worked with Martha White. Alan's expertise and research interests encompass value alignment and AI governance. He is currently exploring the measurement of harms from language models and the incentives that agents

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01:20:14

#93 Prof. MURRAY SHANAHAN - Consciousness,...

Machine Learning Street Talk (MLST) ·

2022/12/24

Support us! https://www.patreon.com/mlst Professor Murray Shanahan is a renowned researcher on sophisticated cognition and its implications for artificial intelligence. His 2016 article ‘Conscious Exotica’ explores the Space of Possible Minds, a concept first proposed by philosopher Aaron Sloman in 1984, which includes all the different forms of minds from those of other animals to those of artificial intelligence. Shanahan rejects the idea of an impenetrable realm of subjective experience and

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00:51:31

#92 - SARA HOOKER - Fairness, Interpretability,...

Machine Learning Street Talk (MLST) ·

2022/12/23

Support us! https://www.patreon.com/mlst Sara Hooker is an exceptionally talented and accomplished leader and research scientist in the field of machine learning. She is the founder of Cohere For AI, a non-profit research lab that seeks to solve complex machine learning problems. She is passionate about creating more points of entry into machine learning research and has dedicated her efforts to understanding how progress in this field can be translated into reliable and accessible machine learning

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00:21:14

#91 - HATTIE ZHOU - Teaching Algorithmic Reasoning...

Machine Learning Street Talk (MLST) ·

2022/12/20

Support us! https://www.patreon.com/mlst Hattie Zhou, a PhD student at Université de Montréal and Mila, has set out to understand and explain the performance of modern neural networks, believing it a key factor in building better, more trusted models. Having previously worked as a data scientist at Uber, a private equity analyst at Radar Capital, and an economic consultant at Cornerstone Research, she has recently released a paper in collaboration with the Google Brain team, titled ‘Teaching

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00:53:47

(Music Removed) #90 - Prof. DAVID CHALMERS -...

Machine Learning Street Talk (MLST) ·

2022/12/19

Support us! https://www.patreon.com/mlst (On the main version we released; the music was a tiny bit too loud in places, and some pieces had percussion which was a bit distracting -- here is a version with all music removed so you have the option! ) David Chalmers is a professor of philosophy and neural science at New York University, and an honorary professor of philosophy at the Australian National University. He is the co-director of the Center for Mind, Brain, and Consciousness, as well as the

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00:53:47

#90 - Prof. DAVID CHALMERS - Consciousness in LLMs...

Machine Learning Street Talk (MLST) ·

2022/12/19

Support us! https://www.patreon.com/mlst David Chalmers is a professor of philosophy and neural science at New York University, and an honorary professor of philosophy at the Australian National University. He is the co-director of the Center for Mind, Brain, and Consciousness, as well as the PhilPapers Foundation. His research focuses on the philosophy of mind, especially consciousness, and its connection to fields such as cognitive science, physics, and technology. He also investigates areas such

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01:21:59

#88 Dr. WALID SABA - Why machines will never rule the...

Machine Learning Street Talk (MLST) ·

2022/12/16

Support us! https://www.patreon.com/mlst Dr. Walid Saba recently reviewed the book Machines Will Never Rule The World, which argues that strong AI is impossible. He acknowledges the complexity of modeling mental processes and language, as well as interactive dialogues, and questions the authors' use of "never." Despite his skepticism, he is impressed with recent developments in large language models, though he questions the extent of their success. We then discussed the successes of cognitive

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