ML Machine Learning Street Talk

Podcast

Machine Learning Street Talk

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 appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).

Website ↗ Last published 2 November 2026 273 posts collected by Sputnik

Said on Machine Learning Street Talk

“I think that the LLMs have now reached a point where they're memetically more powerful than many human minds are… many human beings are professional prompt completers, right? They're incapable of having a single original creative thought. Instead, they are trying to serve expectations of the environment.” — Joscha Bach, Machine Learning Street Talk
Joscha Bach · 2 Nov 2026 Listen →
“I think we do have zombies already. I think the chess program is a zombie. You cannot train a human being to play chess without the human being being conscious. But you can train a computer to play chess without the computer being conscious.” — Joscha Bach, Machine Learning Street Talk
Joscha Bach · 2 Nov 2026 Listen →
“Hales invests 20 person years in formalizing his Kepler conjecture result. And at the end, all he gets out of it is assurance that the thing is correct. Now, that is like, that's much less exciting than getting new math and new discoveries. … So in most cases, mathematicians know when things are right or not. They're not troubled by correctness.” — Kevin Hartnett, Machine Learning Street Talk
Kevin Hartnett · 26 Oct 2026 Listen →
“I think people in AI I've noticed tend to think of evolution in general as this very dumb, naive algorithm that you use when you can't do gradient descent, right? And they basically call it just random search. And I would just want to clarify: evolution is anything but random. … if you solve like even one part of a puzzle and you hang on to that and you search for the other ones, you can turn your exponential search problem into a linear search problem.” — Akarsh Kumar, Machine Learning Street Talk
Akarsh Kumar · 10 Oct 2026 Listen →
“One of my academic brothers, he says, software is only fun if the software doesn't have to work. If it has to work, the fun disappears very quickly.” — Leonardo de Moura, Machine Learning Street Talk
Leonardo de Moura · 30 Sep 2026 Listen →
“We see the code it generated exactly. It's like an alien code, spaghetti. But for some reason, it generalizes really well… It generalized better than our, we would argue, more elegant, hand-tuned harness.” — Zhengyao Jiang, Machine Learning Street Talk
Zhengyao Jiang · 26 Sep 2026 Listen →
“I don't think that move 37 was creative. I think that move 37 was innovative without being creative.” — Edward Hughes, Machine Learning Street Talk
Edward Hughes · 11 Sep 2026 Listen →
“I suspect that the models do kind of know a lot of the time that the thing they're doing is probably a bit sketchy.” — Tom McGrath, Machine Learning Street Talk
Tom McGrath · 2 Sep 2026 Listen →
“My main problem with the word hallucination is it implies that when a hallucination occurs, something different is happening than its normal functioning.” — Adam Becker, Machine Learning Street Talk
Adam Becker · 20 Aug 2026 Listen →
“the one thing that you can always say about any exponential trend, the one thing that's always true, is that they end.” — Adam Becker, Machine Learning Street Talk
Adam Becker · 20 Aug 2026 Listen →

Hosts

Machine Learning Street Talk is hosted by Tim Scarfe , Keith Duggar , Yannic Kilcher , Connor Shorten , Alex Stenlake and Sayak Paul .

Recent Episodes

  1. 2 Nov 2026

    Why Leibniz Couldn't Find the Mind Inside the Mill (Joscha Bach)

    With Joscha Bach

  2. 26 Oct 2026

    Mathematics Just Changed Forever — Kevin Hartnett

    With Kevin Hartnett

  3. 10 Oct 2026

    What Most People Get Wrong About Evolution | Akarsh Kumar

    With Akarsh Kumar

  4. 1 Oct 2026

    How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

  5. 30 Sep 2026

    Who Checks a Proof No Human Can Read? — Leo de Moura

    With Leonardo de Moura

  6. 26 Sep 2026

    When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

    With Zhengyao Jiang

  7. 23 Sep 2026

    How Deep Learning Finally Cracked Messy Tables - Frank Hutter

    With Frank Hutter

  8. 21 Sep 2026

    Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick

    With Alexander Mattick

  9. 15 Sep 2026

    How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu

    With Ming-Yu Liu

  10. 14 Sep 2026

    Speech Recognition Is Not a Solved Problem — Pavan Muddireddy

    With Pavankumar Reddy Muddireddy

  11. 11 Sep 2026

    How Replication Could Teach Machines What Good Science Looks Like — Edward Hughes

    With Edward Hughes

  12. 8 Sep 2026

    AI 2040: Plan A report - Daniel Kokotajlo & Thomas Larsen

    With Daniel Kokotajlo and Thomas Larsen

Guests

Connor Leahy (9 episodes), Karl Friston (7 episodes), Walid Saba (6 episodes), Gary Marcus (6 episodes), Pedro Domingos (5 episodes), Joscha Bach (5 episodes), Francois Chollet (4 episodes), Randall Balestriero (4 episodes), Kenneth Stanley (4 episodes), Stephen Wolfram (4 episodes), Alexander Mattick (3 episodes), Jeff Beck (3 episodes), and 216 more.