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In the latest report, the remaining 1% of attention can include unpublished topics and podcasts with no qualifying discussion.

2 topics highlighted · Sep 28–Oct 4, 2026

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

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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 CasesResearch: Gaining attention in the latest reportResearchAgents: About the same in the latest reportAgentsSafety & governance: Losing attention in the latest reportSafety & governanceHardware: Gaining attention in the latest reportHardwareRegulation: About the same in the latest reportRegulationOpen Models: About the same in the latest reportOpen ModelsEconomics: Losing attention in the latest reportEconomicsInfrastructure: About the same in the latest reportInfrastructureJobs: About the same in the latest reportJobsOther: Below threshold in the latest reportOther

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

Research · 12.4% · Jul 13–19, 2026 · Gaining attention in the latest report

Research

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

Jul 13–19, 2026

12.4%Losing attentionNo comparable prior 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 · Jul 13–19, 2026

A closer read

What changed
This was its first published appearance at 12.4% of the conversation, with evidence across 9 podcasts.
Where it showed up
It appeared in episodes including “Is Kimi K3 Really Fable Class?” and “Kimi K3 Is Here. China Just Hit the AI Frontier.”.
How to read it
6 cited episodes from 5 podcasts are shown below. The topic appeared across 9 podcasts in the full analysis.

Podcast moments from the week

15 quoted moments · 6 episodes · 5 podcasts

Practical AI

The Future of AI Infrastructure with CoreWeave

Open episode ↗
  1. C
    “And so, you know, a bunch of that observability, this is a big part of, I think, where that sort of AI-centric work that sort of, you know, we believe our secret sauce, but certainly everybody's working on that sort of like AI-centric focus on sort of being able to detect thos...”
    Open episode and seek to 17:14

    ConceptResearch

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The AI Daily Brief

The New Enterprise Battle Over Who Owns the Model

Open episode ↗
  1. A
    “Marketing's agent turns competitor moves into landing pages. Sales' agent enriches leads, drafts emails, and updates the CRM. Ops' agent chases the paperwork and tracks the budget. Every agent has access to shared context and follows your rules about scope and approvals. It's ...”
    Open episode and seek to 12:25

    ConceptResearch

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  2. A
    “Now for context, at 975 billion parameters, Inkling is quite a bit smaller than the 1.6 billion parameters of DeepSeek V4 Pro, but a little larger than the 750 billion parameters of ZAI's GLM-5.2. Importantly, TML pre-trained Inkling from scratch. And aside from a small bootst...”
    Open episode and seek to 13:44

    ConceptResearch

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  3. A
    “On coding, Inkling scored 54.3% on SweBench Pro and 63.8% on TerminalBench 2.1, again putting it ahead of NeMoTrON and K2.5, but a little behind K2.6 and at a significant shortfall compared to GLM-5.2, 5.6 SOL, and Fable-5. On GDPVal, which measures real-world tasks and is a s...”
    Open episode and seek to 15:02

    ConceptResearch

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Latent Space

🔬 The Lab of the Future Should Feel Like a Data Center — Andy Beam & Rafa Gómez-Bombarelli, Lila Sciences

Open episode ↗
  1. B
    “those are the types of like serendipity things that we'd actually like to automate”
    Open episode and seek to 46:49

    ConceptResearch

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  2. B
    “We have lots of funny, like, RL fails that are not explicitly reward hacking. Well, I mean, one is when we trained— one of the early things we did was like, can you just like make a plate map? Like, can you like lay the experimental conditions out on a plate. And it got annoye...”
    Open episode and seek to 25:09

    ConceptResearch

    Report this moment
  3. B
    “We are all in on the bitter lesson and scale. We think that methods that scale and that are general beat those that are not. You know, as Ilya said at NeurIPS last year, we have but one internet. It's the fossil fuel we fracked. We got every ounce of data that we could out of ...”
    Open episode and seek to 00:04

    ConceptResearch

    Report this moment

Last Week in AI

#252 - GPT 5.6, Grok 4.5, Nemotron-Labs-Diffusion, AI 2040

Play episode ↗
  1. B
    “So it's causal. It is sometimes referred to as causal.”
    Play from 1:00:00

    ConceptResearch

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  2. B
    “Yeah, it's pretty interesting when you look at like the broad fingerprint of capabilities that's advertised here. So the first thing, by the way, from a You can tell what part of the model announcements I rush to immediately when I see these cyber capabilities, because that's ...”
    Play from 24:27

    ConceptResearch

    Report this moment
  3. A
    “Yeah. And you know, how much does superintelligence help you with stuff building nuclear safely anyways? Onto projects in open source. And we do have a couple of interesting new models that are open source, starting with Nimotron-Labs-Diffusion, a tri-mode language model unify...”
    Play from 55:19

    ConceptResearch

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