The AI conversation, week by week
18 AI-focused podcasts currently tracked18 AI podcasts

Currently tracking18 AI-focused podcasts

  • AI For Humans
  • AI Inside
  • AI Today Podcast
  • Eye on AI
  • Gradient Dissent
  • Interconnects
  • Last Week in AI
  • Latent Space
  • Machine Learning Street Talk
  • Me, Myself, and AI
  • No Priors
  • Practical AI
  • The AI Daily Brief
  • The AI Native Dev
  • The Artificial Intelligence Show
  • The Cognitive Revolution
  • The TWIML AI Podcast
  • Training Data

Trends over time

Jul 13–Oct 4, 2026 · 12 published weeks

In the latest report, the remaining 1% of attention can include unpublished topics and podcasts with no qualifying discussion.

3 topics highlighted · Sep 28–Oct 4, 2026

Select a topic or a dated dot to see its history below.

Swipe to follow the full timeline →

Topic attention across published weeksEach colored line uses the same attention scale. Only topics with published measurements are shown; their shares do not necessarily total 100%. Breaks mean missing measurements, not zero. Dated dots open that topic and week below.0%11.3%22.5%33.8%45%Jul 13Jul 20Jul 27Aug 3Aug 10Aug 17Aug 24Aug 31Sep 7Sep 14Sep 21Sep 28Adoption Use Cases: About the same in the latest reportAdoption Use Cases33.4%Research: Gaining attention in the latest reportResearch22.7%Agents: About the same in the latest reportAgents14.5%Safety & governance: Losing attention in the latest reportSafety & governance8.6%Hardware: Gaining attention in the latest reportHardware7.9%Regulation: About the same in the latest reportRegulation3.9%Open Models: About the same in the latest reportOpen Models3.1%Economics: Losing attention in the latest reportEconomics2.5%Infrastructure: About the same in the latest reportInfrastructure1.2%Jobs: About the same in the latest reportJobs1.2%Other: Below threshold in the latest reportOtherNo measurement

Direction compares the latest report with recent weeks; small changes are “About the same,” and gaps mean no measurement.

Research · 14.8% · Aug 3–9, 2026 · Gaining attention in the latest report

Research

New models, training methods, benchmarks, and discoveries from AI labs.

Aug 3–9, 2026

14.8%About the sameDown 4.5 percentage points from last week

Choose a week to read the discussion.— Below threshold

Research, week by weekDated controls show each week's attention share. Gaps mean no qualifying measurement, not zero. Select a week to read its discussion below.0%11.3%22.5%33.8%45%
Show this week’s discussionHide this week’s discussionPodcast moments and context

Research · Aug 3–9, 2026

A closer read

What changed
Its share fell from 19.3% to 14.8%, with evidence across 12 podcasts.
Where it showed up
It appeared in episodes including “Thinking in Silico: Goodfire CTO Dan Balsam on Concept Manifolds & a $1000/Month ML Research Agent” and “Why People Are Paying 10x More for AI | Sid Sheth, d-Matrix”.
How to read it
6 cited episodes from 5 podcasts are shown below. The topic appeared across 12 podcasts in the full analysis.

Podcast moments from the week

13 quoted moments · 6 episodes · 5 podcasts

The Cognitive Revolution

Thinking in Silico: Goodfire CTO Dan Balsam on Concept Manifolds & a $1000/Month ML Research Agent

Open episode ↗
  1. A
    “I'm just always amazed when I think back to the kind of toy models of superposition is only like 3 years, right, ago now. And we have come so far.”
    Open episode and seek to 04:08

    ConceptResearch

    Report this moment
  2. C
    “where the geometry components come in is that the features aren't like, sort of like naive, maybe like SAE build take on things is like, you could imagine that the model is encoding like a bunch of totally orthogonal concepts to each other”
    Open episode and seek to 14:12

    ConceptResearch

    Report this moment
  3. A
    “I'm guessing it's like most, like the, the different days of the week, I would guess have a very high inner product in the sense, which would to me suggest that they all, the model kind of knows like this is a day of the week sort of thing.”
    Open episode and seek to 18:19

    ConceptResearch

    Report this moment

Eye on AI

Why People Are Paying 10x More for AI | Sid Sheth, d-Matrix

Open episode ↗
  1. A
    “The models have now understood that they have better capability. It's almost like a human being, right? Once you realize that you have acquired a new capability, you become more confident. And same thing with these models. They tend to have become more confident with disagreei...”
    Open episode and seek to 27:03

    ConceptResearch

    Report this moment

No Priors

Chasing Trillion-Dollar Companies, Founder Ambition, Token Budgets, and Regulatory Capture with Sarah & Elad

Play episode ↗
  1. B
    “I think the idea that the models can improve their own training if the leading scientists working on this believe it, and it's an extension of what we are already seeing in code and math, of course you should believe it, right?”
    Play from 18:49

    ConceptResearch

    Report this moment

The Cognitive Revolution

Pick Your Poison: Zvi Mowshowitz on the Unipolar/Multipolar AGI Dilemma, OpenFace & Pacing the ...

Open episode ↗
  1. A
    “it obviously also reflects a major weakness in the models where they have this knowledge cutoff and they don't really know What's going on?”
    Open episode and seek to 15:25

    ConceptResearch

    Report this moment
  2. B
    “The new paper is on some pretty small open models, so it needs replication.”
    Open episode and seek to 2:05:45

    ConceptResearch

    Report this moment
  3. B
    “if you create GPT-3 or even GPT-4 or even GPT-5 via a different method, it's not going to be competitive”
    Open episode and seek to 2:24:52

    ConceptResearch

    Report this moment

AI Inside

What Happens When AI Outsmarts Mathematicians

Play episode ↗
  1. C
    “This is not about language alone. Yes, you can recognize popcorn. But everything else is about understanding how the world operates. And if it had to go over obstacles or found logic in how things operate, then world models matter.”
    Play from 47:24

    ConceptResearch

    Report this moment
  2. B
    “There's so many of them. But, you know, that, you know, potentially using some of that information for training, I imagine systems like this, you know, on different environments and stuff. So, I mean, it should— the video showed the, the, the humanoid had a Ziploc and was dext...”
    Play from 49:49

    ConceptResearch

    Report this moment

Training Data

Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

Play episode ↗
  1. A
    “The first time anyone was able to generate reasonable-looking proteins was the advent of diffusion models. So it was pretty crazy. There were a bunch of generative modeling approaches that would kind of work if you had a bunch of data. So people got these working for images. T...”
    Play from 09:51

    ConceptResearch

    Report this moment
  2. A
    “the whole research process and identifying these types of scaling directions becomes a lot simpler”
    Play from 00:00

    ConceptResearch

    Report this moment
  3. A
    “the whole research process and identifying these types of scaling directions becomes a lot simpler”
    Play from 18:28

    ConceptResearch

    Report this moment
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