Tim Scarfe
Creator & Host, Machine Learning Street Talk
About
Tim Scarfe is the creator and host of Machine Learning Street Talk (MLST), an in-depth technical AI podcast and YouTube channel he started at the beginning of the COVID-19 pandemic in 2020 alongside Yannic Kilcher, Keith Duggar and Connor Shorten. He holds a PhD in machine learning and a first-class degree in computer science, started the software company Dot Net Solutions in 2003, and has since done stints as a Principal Engineer at Microsoft and as Chief Data Scientist at bp. Keith Duggar, who obtained his PhD from MIT and has worked at IBM Research, on Wall Street and at Microsoft, is often his co-interviewer. Scarfe states the show's ethos as "intellectual curiosity, depth, diversity, forward-thinking and production quality", covering symbolic AI, deep learning research, evolutionary methods, AI safety, AI philosophy and highly skeptical positions, and says he deliberately chose not to interview top tech CEOs. His own GitHub profile also lists him as CTO of the augmented-reality company XRAI.
Key Contributions
- Created Machine Learning Street Talk in 2020 and has hosted it since, publishing long-form technical interviews with AI researchers
- Deliberately spans the field's disagreements — symbolic AI, deep learning research, evolutionary methods, AI safety, AI philosophy and highly skeptical positions — rather than one camp
- Says the show covered LLMs, test-time compute, active inference, neurosymbolic models and open-endedness years before they became mainstream
- MLST's conversations in this collection carry Karl Friston on the free energy principle, Jürgen Schmidhuber, Jeff Clune and Ben Goertzel
- Before MLST: founded Dot Net Solutions in 2003, was a Principal Engineer at Microsoft and Chief Data Scientist at bp, and completed a PhD in machine learning
4 conversations they hosted
Connections
Jeff Clune
In conversationProfessor, University of British Columbia
Two hours on the argument that organises Clune's whole career: asking humans to design intelligence is asking for faster horses, and the alternative is open-ended Darwinian search in spaces rich enough to keep generating their own challenges. The conversation runs to where his co-founding of Recursive begins — what it means, and what it risks, to hand AI research to AI.
youtube.com
Ben Goertzel
In conversationFounder & CEO, SingularityNET
Goertzel uses the episode to state his disagreement with Ray Kurzweil precisely: Kurzweil puts human-level AGI at 2029 and the singularity at 2045, and Goertzel thinks that sixteen-year gap is an artefact of fitting a curve to human inventors. Once the AGI is doing the inventing — designing its own chips, its own networking — the exponent changes and the gap collapses to a few years. It is a specific, dateable quarrel between two people on this site.
youtube.com
Jürgen Schmidhuber
In conversationDirector, KAUST AI Initiative & Scientific Director, IDSIA
An episode titled, without hedging, The Man Who Invented Modern AI (Before Everyone Else) — which is both Schmidhuber's own long-running argument and the thing most interviewers decline to say out loud. Giving him the floor to make the priority case at length is the point: the history of deep learning is older and less Anglo-American than its prize citations suggest, and he is its most relentless keeper.
youtube.com
Karl Friston
In conversationNeuroscientist & Theoretical Biologist
The free energy principle is famously difficult to get a clean statement of — a single idea claiming to cover perception, action, learning and the persistence of living things, usually encountered through equations or through paraphrase that loses it. An episode that does nothing but let Friston lay it out at length is a genuine service, and it is why this channel keeps turning up in the citations on this site.
youtube.com
