Rephonic
Artwork for Machine Learning Street Talk

Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)
Deep Learning
Artificial Intelligence
Machine Learning
Cognition
Neural Networks
Social Media
AI Ethics
Mimetics
Societal Progress
Agency and Power
Social Institutions
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

PublishesTwice monthlyEpisodes231Founded5 years ago
Number of ListenersCategory
Technology

Listen to this Podcast

Artwork for Machine Learning Street Talk

Latest Episodes

We sat down with Sara Saab (VP of Product at Prolific) and Enzo Blindow (VP of Data and AI at Prolific) to explore the critical role of human evaluation in AI development and the challenges of aligning AI systems with human values. Prolific is a huma... more

Dr. Ilia Shumailov - Former DeepMind AI Security Researcher, now building security tools for AI agents

Ever wondered what happens when AI agents start talking to each other—or worse, when they start breaking things? Ilia Shumailov spent years at Dee... more

We need AI systems to synthesise new knowledge, not just compress the data they see. Jeremy Berman, is a research scientist at Reflection AI and recent winner of the ARC-AGI v2 public leaderboard.**SPONSOR MESSAGES**—Take the Prolific human data surv... more

Professor Andrew Wilson from NYU explains why many common-sense ideas in artificial intelligence might be wrong. For decades, the rule of thumb in machine learning has been to fear complexity. The thinking goes: if your model has too many parameters ... 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.

Recent Guests

Sara Saab
VP of Product at Prolific, cognitive scientist and philosopher.
Prolific
Episode: Why AI Needs Culture (Not Just Data) [Sponsored] (Sara Saab, Enzo Blindow - Prolific)
Enzo Blindow
VP of Data and AI at Prolific with a background in economic science and computer science.
Prolific
Episode: Why AI Needs Culture (Not Just Data) [Sponsored] (Sara Saab, Enzo Blindow - Prolific)
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)
Akarsh Kumar
A third-year PhD student at MIT interested in emergence and open-ended processes.
MIT
Episode: The Fractured Entangled Representation Hypothesis (Kenneth Stanley, Akarsh Kumar)
Eiso Kant
Co-founder and CTO of Poolside AI
Poolside AI
Episode: Eiso Kant (CTO poolside) - Superhuman Coding Is Coming!
Mohamed Osman
Co-founder of MindsAI and researcher at Tufa AI Labs
Tufa AI Labs
Episode: Test-Time Adaptation: the key to reasoning with DL (Mohamed Osman)

Host

Tim Scarfe
Host with a Ph.D. focused on machine learning and artificial intelligence discussions. Regularly engages in deep, analytical conversations about AI, neuroscience, and philosophy with a diverse range of esteemed guests.

Reviews

4.8 out of 5 stars from 678 ratings
  • Host talks too much, cuts off guests and talks about all his Twitter posts and books ad nausea.

    Podcast Addict
    2
    Locke
    2 months ago
  • Early episodes are a great listen. Last year it felt more like each episode was sponsored.

    Podcast Addict
    2
    kretyn
    2 months ago
  • Was great

    I used to love this but it’s starting to come off as a platform for product promotion webinars. I don’t know what’s in it for the creator but it has lost my trust. I’ll still check with interest for good content and of course there are always things to learn amongst the marketing bullets but I miss the earlier days here.

    Apple Podcasts
    2
    RandomUserOfYourApp
    United Statesa year ago
  • A great podcast without much fluff or product placements.

    Podcast Addict
    5
    kretyn
    a year ago
  • Generally good but episode with Maria was awful

    Maria’s anti-AI denialism was ridiculous. Generally I like to hear people from outside the field. But she stated her position with complete certainty and no reasoned arguments at all and spoke of areas she clearly had no knowledge

    . She was arrogant and insulted listeners intelligence. There are dangers in AI but her arguments were paper thin. The arguments that we can write without thinking is ridiculous. Does she know that her subconscious is working hard. Then she said China’s autocracy was ... more

    Apple Podcasts
    1
    Adrian1423
    United Kingdoma year ago

Listeners Say

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

Some listeners are expressing concerns about the shift toward sponsored content, with critiques suggesting recent episodes feel more commercialized than before.
Listeners appreciate the depth of discussions and the caliber of guests involved, often highlighting the intellectual rigor of the content.
The show is recognized for its informative nature, with many praising the hosts' ability to navigate complex topics without oversimplifying.

Chart Rankings

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

Apple Podcasts
#140
United States/Technology
Spotify
#47
United Kingdom/Technology
Apple Podcasts
#231
United Kingdom/Technology
Apple Podcasts
#87
Germany/Technology
Apple Podcasts
#111
Italy/Technology
Apple Podcasts
#207
Australia/Technology

Talking Points

Recent interactions between the hosts and their guests.

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.
Karl Friston - Why Intelligence Can't Get Too Large (Goldilocks principle)
Q: How's it been going? What could have gone better over the last 20-odd years in relation to the Free Energy Principle?
Friston expresses ambivalence over the difficulties in communicating the Free Energy Principle due to its complexity, indicating that while it's crucial to engage people's curiosity, it should ideally be simple to understand.

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?

Focusing on advanced discussions surrounding artificial intelligence, neuroscience, and cognitive science, analytical conversations engage with leading experts in the field. The show aims for a comprehensive exploration of cutting-edge topics, offering a nuanced perspective that often contrasts with mainstream narratives. This podcast stands out for its commitment to intellectual diversity, combining rigorous inquiries into philosophical concepts with applied considerations in technology and AI. Listeners can expect a deep dive into the philosophical implications of AI advancements, ethical considerations, and the exploration of consciousness and intelligence, making it a rich resource for both enthusiasts and professionals in the area.

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How many episodes of Machine Learning Street Talk are there?

Machine Learning Street Talk launched 5 years ago and published 231 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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What guests have appeared on Machine Learning Street Talk?

Recent guests on Machine Learning Street Talk include:

1. Sara Saab
2. Enzo Blindow
3. Andrew Gordon Wilson
4. Karl Friston
5. Michael Timothy Bennett
6. Dan Hendrycks
7. Akarsh Kumar
8. Eiso Kant

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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