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Artwork for Machine Learning Street Talk

Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)
Deep Learning
Artificial Intelligence
Machine Learning
Neural Networks
AI Ethics
Social Media
IAC Movement
Entropy
Effective Altruism
Technology
Societal Progress
Agency
Divergence
Cognitive Science
Generative Models
Intelligence
Creativity
Free Energy Principle
Ethics In AI
Maven

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

PublishesWeeklyEpisodes249Founded6 years ago
Number of ListenersCategory
Technology

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Artwork for Machine Learning Street Talk

Latest Episodes

Robert Lange, founding researcher at Sakana AI, joins Tim to discuss *Shinka Evolve* — a framework that combines LLMs with evolutionary algorithms to do open-ended program search. The core claim: systems like AlphaEvolve can optimize solutions to fix... more

Dive into the realities of AI-assisted coding, the origins of modern fine-tuning, and the cognitive science behind machine learning with fast.ai founder Jeremy Howard. In this episode, we unpack why AI might be turning software engineering into a slo... more

What if life itself is just a really sophisticated computer program that wrote itself into existence?

Blaise Agüera y Arcas presenting at ALife 2025 — the most technically detailed public walkthrough of the ideas in his *What is Life?* and *What is ... more

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 age... more

Key Facts

Accepts Guests
Accepts Sponsors
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

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Recent Guests

Mazviita Chirimuuta
A philosopher who teaches at Edinburgh University
University of Edinburgh
Episode: Why Every Brain Metaphor in History Has Been Wrong [SPECIAL EDITION]
Max Bennett
Author and expert in neuroscience
Episode: Your Brain is Running a Simulation Right Now [Max Bennett]
Chris Kempes
Professor at the Santa Fe Institute
Santa Fe Institute
Episode: The Universal Hierarchy of Life - Prof. Chris Kempes [SFI]
Sara Saab
VP of Product at Prolific, cognitive scientist and philosopher.
Prolific
Episode: The Secret Engine of AI - Prolific [Sponsored] (Sara Saab, Enzo Blindow)
Enzo Blindow
VP of Data and AI at Prolific with a background in economic science and computer science.
Prolific
Episode: The Secret Engine of AI - Prolific [Sponsored] (Sara Saab, Enzo Blindow)
Andrew Gordon Wilson
Professor at the Cron Institute of Mathematical Sciences and Center for Data Science at New York University
New York University
Episode: Deep Learning is Not So Mysterious or Different - Prof. Andrew Gordon Wilson (NYU)
Karl Friston
A renowned neuroscientist known for his work on the Free Energy Principle.
Episode: Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)
Michael Timothy Bennett
Computer scientist focused on AI, intelligence, life, the universe, and the nature of existence.
Episode: Michael Timothy Bennett: Defining Intelligence and AGI Approaches
Dan Hendrycks
Co-author of the Superintelligence Strategy paper
NA
Episode: Superintelligence Strategy (Dan Hendrycks)

Host

Tim Scarfe
Host and producer with expertise in machine learning and artificial intelligence discussions.

Reviews

4.8 out of 5 stars from 725 ratings
  • 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 Podcasts
    1
    Leopold P Bloom
    United States2 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 Podcasts
    5
    Bzeev
    Germany2 months ago
  • 😎😎

    норм подкастик. много свежих инсайтов

    Apple Podcasts
    5
    Вода Природная
    Russia2 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 Podcasts
    2
    DePrincipatibus
    Germany4 months ago
  • The Host is pretty biased / episodes that are just not understandable

    The host is just against LLMs. Also, he has on some professors and they discuss fully specific PhD stuff, and it’s just not listenable

    Apple Podcasts
    3
    Awsedrftgyhujikolm
    United States5 months ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Intellectually stimulating discussions on AI and related fields.
Some listeners express concern regarding recent shifts towards sponsored content.
Hosts bring a wide range of expertise, contributing to rich dialogues.
Common praise for insightful guests and their diverse backgrounds.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#100
United States/Technology
Spotify
#48
United Kingdom/Technology
Apple Podcasts
#50
United Kingdom/Technology
Apple Podcasts
#129
Canada/Technology
Apple Podcasts
#72
France/Technology
Apple Podcasts
#79
Australia/Technology

Talking Points

Recent interactions between the hosts and their guests.

Bayesian Brain, Scientific Method, and Models [Dr. Jeff Beck]
Q: What do you think about these broad sort of metaphorical idealizations?
The brain is a prediction machine; the nature of our explanations for how the brain works will align with the most sophisticated technology available.
AI Agents Can Code 10,000 Lines of Hacking Tools In Seconds - Dr. Ilia Shumailov (ex-GDM)
Q: What do you think about the open source thing?
While there might be benefits from openly available platforms, Shumailov expresses concerns about security risks associated with uncontrolled access to diverse AI models.
New top score on ARC-AGI-2-pub (29.4%) - Jeremy Berman
Q: Can you tell the audience a little bit about yourself and maybe we should start with your first ARC solution?
Jeremy Berman discusses his journey into research, his previous role as a CTO, and how he transitioned to focus on artificial general intelligence and the ARC challenge.
Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)
Q: What would it mean to be conscious?
Friston articulates that it might involve having posterior beliefs that are precise in a dynamical sense, influenced by neurobiological evidence.
Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)
Q: Do you think we can build machines that have understanding, that have consciousness?
Friston believes it is possible in principle but emphasizes the need for machines to have a long temporal depth in their generative models to approach true consciousness.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

Listeners per Episode
Gender Skew
Location
Interests
Professions
Age Range
Household Income
Social Media Reach

Frequently Asked Questions About Machine Learning Street Talk

What is Machine Learning Street Talk about and what kind of topics does it cover?

Engaging conversations unfold with pre-eminent figures in artificial intelligence, cognitive science, and philosophy. The discussions emphasize a rigorous examination of contemporary topics, shedding light on current affairs within the AI landscape while stripping away the hype often surrounding these subjects. A strong focus on intellectual diversity leads to the exploration of various ideas, including the philosophical implications of advancements in AI and neuroscience. Over time, episodes have included in-depth analyses that challenge traditional perceptions while inviting a broad array of viewpoints to encourage more profound insights.

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How many listeners does Machine Learning Street Talk get?

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How many subscribers and views does Machine Learning Street Talk have?

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Which podcasts are similar to Machine Learning Street Talk?

These podcasts share a similar audience with Machine Learning Street Talk:

1. Dwarkesh Podcast
2. Practical AI
3. The AI Daily Brief: Artificial Intelligence News and Analysis
4. Conversations with Tyler
5. The a16z Show

How many episodes of Machine Learning Street Talk are there?

Machine Learning Street Talk launched 6 years ago and published 249 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?

Our systems regularly scour the web to find email addresses and social media links for this podcast. We scanned the web and collated all of the contact information that we could find in our podcast database. But in the unlikely event that you can't find what you're looking for, our concierge service lets you request our research team to source better contacts for you.

Where can I see ratings and reviews 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. Mazviita Chirimuuta
2. Max Bennett
3. Chris Kempes
4. Sara Saab
5. Enzo Blindow
6. Andrew Gordon Wilson
7. Karl Friston
8. Michael Timothy Bennett

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.

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