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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: 189

Nora Belrose, Head of Interpretability Research at EleutherAI, discusses critical challenges in AI s

Prof. Gennady Pekhimenko (CEO of CentML, UofT) joins us in this *sponsored episode* to dive deep int

Prof. Gennady Pekhimenko (CEO of CentML, UofT) joins us in this *sponsored episode* to dive deep int

Eliezer Yudkowsky and Stephen Wolfram discuss artificial intelligence and its potential existen‑ tia

Francois Chollet, a prominent AI expert and creator of ARC-AGI, discusses intelligence, consciousnes

Anil Ananthaswamy is an award-winning science writer and former staff writer and deputy news editor

Professor Michael Levin explores the revolutionary concept of diverse intelligence, demonstrating ho

Will Williams is CTO of Speechmatics in Cambridge. In this sponsored episode - he shares deep techni

Dr. Sanjeev Namjoshi, a machine learning engineer who recently submitted a book on Active Inference

Dr. Joscha Bach discusses advanced AI, consciousness, and cognitive modeling. He presents consciousn

Alessandro Palmarini is a post-baccalaureate researcher at the Santa Fe Institute working under the

François Chollet discusses the limitations of Large Language Models (LLMs) and proposes a new approa

Ivan Zhang, co-founder of Cohere, discusses the company's enterprise-focused AI solutions. He explai

Prof. Tim Rocktäschel, AI researcher at UCL and Google DeepMind, talks about open-ended AI systems.

Ben Goertzel discusses AGI development, transhumanism, and the potential societal impacts of superin

AI expert Prof. Gary Marcus doesn't mince words about today's artificial intelligence. He ar

Prof. Mark Solms, a neuroscientist and psychoanalyst, discusses his groundbreaking work on conscious

Dr. Patrick Lewis, who coined the term RAG (Retrieval Augmented Generation) and now works at Cohere,

Ashley Edwards, who was working at DeepMind when she co-authored the Genie paper and is now at Runwa

Saurabh Baji discusses Cohere's approach to developing and deploying large language models (LLMs