
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... more
| Publishes | Twice monthly | Episodes | 259 | Founded | 6 years ago |
|---|---|---|---|---|---|
| Number of Listeners | Category | Technology | |||

Astrophysicist Adam Becker, author of "What Is Real?", joins Tim Scarfe to take apart the futures Silicon Valley keeps selling: the 2045 singularity, mind uploading, Mars colonies, and the AI apocalypse. His new book *More Everything Forever* argues ... more
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at notion.com/mlstWhy can deep networks discover abstractions that shallow models miss? Statistical physicist Matthieu Wyart joins Tim Scarfe to argue tha... more
Can an AI do the right thing for the wrong reason? Tim Scarfe speaks with Apollo Research’s Alexander Meinke, Axel Højmark and Jérémy Scheurer about Measuring Reward-Seeking via Contrastive Belief Updates, their new research with OpenAI.
The panel a... more
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at notion.com/mlst
Britain's most capable coding model can't be exported, and that ban is the whole reason Cosine set out to build one from scratch. Alis... more
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This podcast is a gem. It is much more than ml
The person who moderated (or failed to) the Wolfram and Yudkowsy conversation wasted both guests and the audience’s time
I really enjoy Machine Learning Street Talk, even when I don’t agree with every opinion.
I’m curious what happens when we add quantum mechanics to the discussion.
I’d love to hear your thoughts.
Boaz Kaizman, artist, Cologne
норм подкастик. много свежих инсайтов
It used to be one of my favourite ML podcasts, with genuinely in-depth discussions and fascinating guests. Over time, though, it became increasingly clear that its primary goal had shifted to revenue generation, and the quality of the interviews declined accordingly. At its worst, entire episodes felt like thinly veiled sponsored ads for overhyped startups. It’s genuinely disappointing to watch such a once-excellent podcast lose its way.
Key themes from listener reviews, highlighting what works and what could be improved about the show.
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Apple Podcasts | #112 | |
Spotify | #50 | |
Apple Podcasts | #78 | |
Apple Podcasts | #87 | |
Apple Podcasts | #68 | |
Apple Podcasts | #84 |
Recent interactions between the hosts and their guests.
Listeners, social reach, demographics and more for this podcast.
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A rigorous tech and ideas podcast featuring deep dives into AI, cognitive science, neuroscience, and philosophy of mind. Episodes commonly explore safety, governance, abstraction, and the implications of frontier AI, often with industry researchers, philosophers, and seasoned practitioners as guests. The show is known for technical depth, broad intellectual curiosity, and a critical stance toward hype, with occasional critiques about sponsorship and production that shape listener perceptions. Potential listeners who want thoughtful, theory-to-practice discussions on AI and its broader human implications will likely find it compelling, while those seeking lighter or more promotional formats may feel differently.</summary
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Machine Learning Street Talk launched 6 years ago and published 259 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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Recent guests on Machine Learning Street Talk include:
1. Alistair Pullen
2. Thomas Ahle
3. John Jumper
4. Emmanuel Nji
5. Anthony Aguirre
6. Michael I. Jordan
7. Beth Barnes
8. David Rein
To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.