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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

00:46:56

VAEs Are Energy-Based Models? [Dr. Jeff Beck]

Machine Learning Street Talk (MLST) ·

2026/01/25

What makes something truly *intelligent?* Is a rock an agent? Could a perfect simulation of your brain actually *be* you? In this fascinating conversation, Dr. Jeff Beck takes us on a journey through the philosophical and technical foundations of agency, intelligence, and the future of AI.Jeff doesn't hold back on the big questions. He argues that from a purely mathematical perspective, there's no structural difference between an agent and a rock – both execute policies that map inputs to

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00:53:37

Abstraction & Idealization: AI's Plato Problem...

Machine Learning Street Talk (MLST) ·

2026/01/23

Professor Mazviita Chirimuuta joins us for a fascinating deep dive into the philosophy of neuroscience and what it really means to understand the mind.*What can neuroscience actually tell us about how the mind works?* In this thought-provoking conversation, we explore the hidden assumptions behind computational theories of the brain, the limits of scientific abstraction, and why the question of machine consciousness might be more complicated than AI researchers assume.Mazviita, author of *The Brain

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00:42:04

Why Every Brain Metaphor in History Has Been Wrong...

Machine Learning Street Talk (MLST) ·

2026/01/23

What if everything we think we know about the brain is just a really good metaphor that we forgot was a metaphor?This episode takes you on a journey through the history of scientific simplification, from a young Karl Friston watching wood lice in his garden to the bold claims that your mind is literally software running on biological hardware.We bring together some of the most brilliant minds we've interviewed — Professor Mazviita Chirimuuta, Francois Chollet, Joscha Bach, Professor Luciano

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01:16:37

We Invented Momentum Because Math is Hard [Dr. Jeff...

Machine Learning Street Talk (MLST) ·

2025/12/31

Dr. Jeff Beck, mathematician turned computational neuroscientist, joins us for a fascinating deep dive into why the future of AI might look less like ChatGPT and more like your own brain.**SPONSOR MESSAGES START**—Prolific - Quality data. From real people. For faster breakthroughs.https://www.prolific.com/?utm_source=mlst—**END***What if the key to building truly intelligent machines isn't bigger models, but smarter ones?*In this conversation, Jeff makes a compelling case that we've been

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03:17:09

Your Brain is Running a Simulation Right Now [Max...

Machine Learning Street Talk (MLST) ·

2025/12/30

Tim sits down with Max Bennett to explore how our brains evolved over 600 million years—and what that means for understanding both human intelligence and AI.Max isn't a neuroscientist by training. He's a tech entrepreneur who got curious, started reading, and ended up weaving together three fields that rarely talk to each other: comparative psychology (what different animals can actually do), evolutionary neuroscience (how brains changed over time), and AI (what actually works in

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01:37:05

The 3 Laws of Knowledge [César Hidalgo]

Machine Learning Street Talk (MLST) ·

2025/12/27

César Hidalgo has spent years trying to answer a deceptively simple question: What is knowledge, and why is it so hard to move around?We all have this intuition that knowledge is just... information. Write it down in a book, upload it to GitHub, train an AI on it—done. But César argues that's completely wrong. Knowledge isn't a thing you can copy and paste. It's more like a living organism that needs the right environment, the right people, and constant exercise to survive.Guest: César

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02:55:46

"I Desperately Want To Live In The Matrix" - Dr. Mike...

Machine Learning Street Talk (MLST) ·

2025/12/24

This is a lively, no-holds-barred debate about whether AI can truly be intelligent, conscious, or understand anything at all — and what happens when (or if) machines become smarter than us.Dr. Mike Israetel is a sports scientist, entrepreneur, and co-founder of RP Strength (a fitness company). He describes himself as a "dilettante" in AI but brings a fascinating outsider's perspective.Jared Feather (IFBB Pro bodybuilder and exercise physiologist)The Big Questions:1. When is

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00:43:57

Making deep learning perform real algorithms with...

Machine Learning Street Talk (MLST) ·

2025/12/22

We often think of Large Language Models (LLMs) as all-knowing, but as the team reveals, they still struggle with the logic of a second-grader. Why can’t ChatGPT reliably add large numbers? Why does it "hallucinate" the laws of physics? The answer lies in the architecture. This episode explores how *Category Theory* —an ultra-abstract branch of mathematics—could provide the "Periodic Table" for neural networks, turning the "alchemy" of modern AI into a rigorous science.In this deep-dive exploration,

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00:16:04

Are AI Benchmarks Telling The Full Story? [SPONSORED]...

Machine Learning Street Talk (MLST) ·

2025/12/20

Is a car that wins a Formula 1 race the best choice for your morning commute? Probably not. In this sponsored deep dive with Prolific, we explore why the same logic applies to Artificial Intelligence. While models are currently shattering records on technical exams, they often fail the most important test of all: **the human experience.**Why High Benchmark Scores Don’t Mean Better AIJoining us are **Andrew Gordon** (Staff Researcher in Behavioral Science) and **Nora Petrova** (AI Researcher) from

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01:39:14

The Mathematical Foundations of Intelligence...

Machine Learning Street Talk (MLST) ·

2025/12/13

What if everything we think we know about AI understanding is wrong? Is compression the key to intelligence? Or is there something more—a leap from memorization to true abstraction? In this fascinating conversation, we sit down with **Professor Yi Ma**—world-renowned expert in deep learning, IEEE/ACM Fellow, and author of the groundbreaking new book *Learning Deep Representations of Data Distributions*. Professor Ma challenges our assumptions about what large language models actually do, reveals why

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01:27:48

Pedro Domingos: Tensor Logic Unifies AI Paradigms

Machine Learning Street Talk (MLST) ·

2025/12/08

Pedro Domingos, author of the bestselling book "The Master Algorithm," introduces his latest work: Tensor Logic - a new programming language he believes could become the fundamental language for artificial intelligence.Think of it like this: Physics found its language in calculus. Circuit design found its language in Boolean logic. Pedro argues that AI has been missing its language - until now.**SPONSOR MESSAGES START**—Build your ideas with AI Studio from Google -

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01:12:39

"I Invented the Transformer. Now I'm Replacing It." &...

Machine Learning Street Talk (MLST) ·

2025/11/23

The Transformer architecture (which powers ChatGPT and nearly all modern AI) might be trapping the industry in a localized rut, preventing us from finding true intelligent reasoning, according to the person who co-invented it. Llion Jones and Luke Darlow, key figures at the research lab Sakana AI, join the show to make this provocative argument, and also introduce new research which might lead the way forwards.**SPONSOR MESSAGES START**—Build your ideas with AI Studio from Google -

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00:24:19

Why Humans Are Still Powering AI [Sponsored]

Machine Learning Street Talk (MLST) ·

2025/11/03

Ever wonder where AI models actually get their "intelligence"? We reveal the dirty secret of Silicon Valley: behind every impressive AI system are thousands of real humans providing crucial data, feedback, and expertise.Guest: Phelim Bradley, CEO and Co-founder of ProlificPhelim Bradley runs Prolific, a platform that connects AI companies with verified human experts who help train and evaluate their models. Think of it as a sophisticated marketplace matching the right human expertise to

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00:40:59

The Universal Hierarchy of Life - Prof. Chris Kempes...

Machine Learning Street Talk (MLST) ·

2025/10/25

"What is life?" - asks Chris Kempes, a professor at the Santa Fe Institute.Chris explains that scientists are moving beyond a purely Earth-based, biological view and are searching for a universal theory of life that could apply to anything, anywhere in the universe. He proposes that things we don't normally consider "alive"—like human culture, language, or even artificial intelligence; could be seen as life forms existing on different "substrates".To understand

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00:59:53

Google Researcher Shows Life "Emerges From Code" -...

Machine Learning Street Talk (MLST) ·

2025/10/21

Blaise Agüera y Arcas explores some mind-bending ideas about what intelligence and life really are—and why they might be more similar than we think (filmed at ALIFE conference, 2025 - https://2025.alife.org/).Life and intelligence are both fundamentally computational (he says). From the very beginning, living things have been running programs. Your DNA? It's literally a computer program, and the ribosomes in your cells are tiny universal computers building you according to those

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01:19:39

The Secret Engine of AI - Prolific [Sponsored] (Sara...

Machine Learning Street Talk (MLST) ·

2025/10/18

We sat down with Sara Saab (VP of Product at Prolific) and Enzo Blindow (VP of Data and AI at Prolific) to explore the critical role of human evaluation in AI development and the challenges of aligning AI systems with human values. Prolific is a human annotation and orchestration platform for AI used by many of the major AI labs. This is a sponsored show in partnership with Prolific. **SPONSOR MESSAGES**—cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the

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01:01:07

AI Agents Can Code 10,000 Lines of Hacking Tools In...

Machine Learning Street Talk (MLST) ·

2025/10/04

Dr. Ilia Shumailov - Former DeepMind AI Security Researcher, now building security tools for AI agentsEver wondered what happens when AI agents start talking to each other—or worse, when they start breaking things? Ilia Shumailov spent years at DeepMind thinking about exactly these problems, and he's here to explain why securing AI is way harder than you think.**SPONSOR MESSAGES**—Check out notebooklm for your research project, it's really powerfulhttps://notebooklm.google.com/—Take the

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01:08:27

New top score on ARC-AGI-2-pub (29.4%) - Jeremy Berman

Machine Learning Street Talk (MLST) ·

2025/09/27

We need AI systems to synthesise new knowledge, not just compress the data they see. Jeremy Berman, is a research scientist at Reflection AI and recent winner of the ARC-AGI v2 public leaderboard.**SPONSOR MESSAGES**—Take the Prolific human data survey - https://www.prolific.com/humandatasurvey?utm_source=mlst and be the first to see the results and benchmark their practices against the wider community!—cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the

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02:03:48

Deep Learning is Not So Mysterious or Different -...

Machine Learning Street Talk (MLST) ·

2025/09/19

Professor Andrew Wilson from NYU explains why many common-sense ideas in artificial intelligence might be wrong. For decades, the rule of thumb in machine learning has been to fear complexity. The thinking goes: if your model has too many parameters (is "too complex") for the amount of data you have, it will "overfit" by essentially memorizing the data instead of learning the underlying patterns. This leads to poor performance on new, unseen data. This is known as the classic

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01:21:39

Karl Friston - Why Intelligence Can't Get Too Large...

Machine Learning Street Talk (MLST) ·

2025/09/10

In this episode, hosts Tim and Keith finally realize their long-held dream of sitting down with their hero, the brilliant neuroscientist Professor Karl Friston. The conversation is a fascinating and mind-bending journey into Professor Friston's life's work, the Free Energy Principle, and what it reveals about life, intelligence, and consciousness itself.**SPONSORS**Gemini CLI is an open-source AI agent that brings the power of Gemini directly into your terminal -

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