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... more
| Publishes | Twice monthly | Episodes | 255 | Founded | 6 years ago |
|---|---|---|---|---|---|
| Number of Listeners | Category | Technology | |||
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Latest Episodes
Tim Scarfe travels to Zurich to sit down with the Tufa Labs ARC-AGI-3 team — founder Benjamin Crouzier, with Jeroen Cottaar, Dries Smit, Stefano Viel and Michal Tesnar — to work out what their leaderboard-topping system does and what the benchmark is... more
Thomas Ahle wants Normal Computing to be the Lovable for chip design: type your intent, and a swarm of agents carries it from design through optimisation, formalisation and verification to tape-out. To get there, his team at wrote their own open-sour... more
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at notion.com/mlstProtein folding stalled biology for fifty years. A sequence of amino acids dictates a three-dimensional shape, but reading that shape me... more
Brad Carson was the Army's General Counsel, served two terms in Congress and was Acting Under Secretary of Defense for Personnel and Readiness. He now heads Americans for Responsible Innovation, the AI-policy advocacy group he co-founded. Keith Dugga... more
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Reviews
- Great
This podcast is a gem. It is much more than ml
Apple Podcasts5Tosvarsan
Sweden20 days ago - You let this happen?!
The person who moderated (or failed to) the Wolfram and Yudkowsy conversation wasted both guests and the audience’s time
Apple Podcasts1Leopold P Bloom
United States6 months ago - quantum mechanics
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
Apple Podcasts5Bzeev
Germany6 months ago - 😎😎
норм подкастик. много свежих инсайтов
Apple Podcasts5Вода Природная
Russia6 months ago - Once-excellent podcast
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.
Apple Podcasts2DePrincipatibusGermany8 months ago
Listeners Say
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Chart Rankings
How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.
Apple Podcasts | #130 | United States/Technology |
Apple Podcasts | #69 |  Canada/Technology |
Apple Podcasts | #127 |  United Kingdom/Technology |
Apple Podcasts | #85 | Germany/Technology |
Apple Podcasts | #113 |  France/Technology |
Apple Podcasts | #16 |  South Africa/Technology |
Talking Points
Recent interactions between the hosts and their guests.
Audience Metrics
Listeners, social reach, demographics and more for this podcast.
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Frequently Asked Questions About Machine Learning Street Talk
What is Machine Learning Street Talk about and what kind of topics does it cover?
A highly technical, cross-disciplinary AI podcast that blends machine learning, cognitive science, neuroscience, and philosophy of mind. Episodes typically center on how social, economic, and governance structures shape AI development, with deep dives into evaluation benchmarks, data markets, and the ethics of automation. Guests span leading researchers, philosophers, and industry thinkers, resulting in rigorous conversations that challenge hype with careful reasoning, practical examples, and nuanced takes on long-term societal implications. A standout trait is the willingness to explore foundational questions—what intelligence is, how to measure it, and how humans should steer powerful technologies—while maintaining accessibility for techn... more
Where can I find podcast stats for Machine Learning Street Talk?
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How many listeners does Machine Learning Street Talk get?
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What are the audience demographics for Machine Learning Street Talk?
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How many subscribers and views does Machine Learning Street Talk have?
To see how many followers or subscribers Machine Learning Street Talk has on Spotify and other platforms such as Castbox and Podcast Addict, simply upgrade your account. You'll also find viewership figures for their YouTube channel if they have one.
Which podcasts are similar to Machine Learning Street Talk?
These podcasts share a similar audience with Machine Learning Street Talk:
1. The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
2. Dwarkesh Podcast
3. No Priors: Artificial Intelligence | Technology | Startups
4. Training Data
5. Practical AI
How many episodes of Machine Learning Street Talk are there?
Machine Learning Street Talk launched 6 years ago and published 255 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
How do I contact Machine Learning Street Talk?
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Where can I see ratings and reviews for Machine Learning Street Talk?
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View all the reviews in one place instead of visiting each platform individually and use this information to decide if a show is worth pitching or not.
How do I access podcast episode transcripts for Machine Learning Street Talk?
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What guests have appeared on Machine Learning Street Talk?
Recent guests on Machine Learning Street Talk include:
1. Thomas Ahle
2. John Jumper
3. Emmanuel Nji
4. Anthony Aguirre
5. Michael I. Jordan
6. Beth Barnes
7. David Rein
8. Robert Lange
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.