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In the latest report, the remaining 1% of attention can include unpublished topics and podcasts with no qualifying discussion.

6 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 · 24% · Aug 17–23, 2026 · Gaining attention in the latest report

Research

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

Aug 17–23, 2026

24%Gaining attentionUp 0.4 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 17–23, 2026

A closer read

What changed
Its share rose from 23.6% to 24%, with evidence across 11 podcasts.
Where it showed up
It appeared in episodes including “Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov” and “AI in the AM — Weekly Highlights: Relaunch Week (Aug 17–20, 2026)”.
How to read it
6 cited episodes from 5 podcasts are shown below. The topic appeared across 11 podcasts in the full analysis.

Podcast moments from the week

16 quoted moments · 6 episodes · 5 podcasts

Machine Learning Street Talk

Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov

Open episode ↗
  1. C
    “This we don't know. There were prior reports by Apollo and by METER where models were like, OpenAI models were like kind of caught doing this. And they're like, first observed that it's okay, we don't know what it means, but they do it. And this is kind of what we now confirme...”
    Open episode and seek to 11:15

    ConceptResearch

    Report this moment
  2. E
    “It sounds very complex. Can you actually explain this once again? Like why, So I'm a model, I reason through a problem, I produce this reasoning blob. And I guess this is not the final answer, or is this the final answer?”
    Open episode and seek to 05:47

    ConceptResearch

    Report this moment
  3. C
    “Measure what? Whether it's coming from RL? Take model before RL and after RL, see how it's doing.”
    Open episode and seek to 14:21

    ConceptResearch

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The Cognitive Revolution

AI in the AM — Weekly Highlights: Relaunch Week (Aug 17–20, 2026)

Open episode ↗
  1. M
    “I don't think tokens are the optimization unit anymore. It is the full trajectory, especially as you think about reasoning models and agents. That becomes much, much more important.”
    Open episode and seek to 2:06:42

    ConceptResearch

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  2. I
    “Is there like a frontier LLM at that level being used to optimize the model? the runtime decisions on an ongoing basis?”
    Open episode and seek to 2:10:43

    ConceptResearch

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  3. I
    “The AIs seem to have developed a little bit their own dialect in the chain of thought, where they're using terms in very odd ways. Bronson describes them as having their own ontology and their own world model. And they seem to use these particular nouns and also verbs in some ...”
    Open episode and seek to 51:28

    ConceptResearch

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Latent Space

Simulation: the new Scaling Law — Joon Sung Park, Simile AI

Open episode ↗
  1. A
    “Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to train a model that's very sparse? You're expecting to do multimillion-dollar runs. Are you thinking about this in a model architecture...”
    Open episode and seek to 51:06

    ConceptResearch

    Report this moment
  2. C
    “accuracy, which is a big improvement over all the other methods that you showed.”
    Open episode and seek to 28:26

    ConceptResearch

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  3. A
    “if the model is saying you should walk to the car wash, you know, Anything here?”
    Open episode and seek to 34:09

    ConceptResearch

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Machine Learning Street Talk

Every Exponential Ends — Silicon Valley Forgot — Adam Becker

Open episode ↗
  1. C
    “these models can do things that we do extremely well. And they seem to be getting better all the time”
    Open episode and seek to 23:34

    ConceptResearch

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  2. B
    “it allowed for a kind of mathematical research that could not have been done before”
    Open episode and seek to 28:20

    ConceptResearch

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  3. C
    “internally they are acquiring during their training process some kind of coarse-grained abstraction, some kind of structure.”
    Open episode and seek to 30:31

    ConceptResearch

    Report this moment

No Priors

From Restoring Sight to Reimagining the Brain, with Max Hodak

Play episode ↗
  1. A
    “I think figuring out where that transition happens is a really compelling area of research for us.”
    Play from 15:17

    ConceptResearch

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  2. B
    “You are of the view that it makes sense that there is this increased, like, uh, interest, this surge of investor interest and founder and engineer interest in BCI as a field, given the progress of AI model research, because the representations actually should be shared, or the...”
    Play from 19:49

    ConceptResearch

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  3. A
    “it is just way easier to do neuroscience on the models”
    Play from 22:07

    ConceptResearch

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AI Inside

OpenAI Pumps the Brakes After Its AI Escaped

Play episode ↗
  1. B
    “There was. I can't remember what it was, but there was one model that was trained only on stuff before a a certain date. Yeah, it was, it was, it was about— well, it was also— there's a, there's a term about it for steel that isn't radioactive that you can get from under the o...”
    Play from 50:47

    ConceptResearch

    Report this moment
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