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The Best Machine Learning Podcasts to Sharpen Your Skills
Last updated: March 2026 In the fast-paced world of machine learning, staying up-to-date with the latest research, tools, and techniques is crucial. Podcasts are an invaluable resource for learning on the go, whether you're commuting, at the gym, or just taking a break. But with so many options out there, finding the best machine learning podcasts can be a challenge. That's where The Podcast App comes in. We've curated a list of the top-rated podcasts to help you level up your skills and knowledge.
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The Best Machine Learning Podcasts in 2026
For practitioners and the seriously curious — research, engineering, and the people pushing ML forward. Listen free in The Podcast App.
Listen to all 12 of these free in The Podcast App — with limited offline listening, no app-inserted ads, and optional AI summaries.
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#1The TWIML AI Podcast
Sam Charrington
Sam Charrington's long-running, technical interviews with machine learning researchers and engineers.
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#2Gradient Dissent
Lukas Biewald
Weights & Biases talks with ML practitioners about getting models from research into production.
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#3The Robot Brains Podcast
Pieter Abbeel
Berkeley's Pieter Abbeel interviews the researchers behind advances in AI and robotics.
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#4Machine Learning Street Talk
Machine Learning Street Talk (MLST)
Rigorous, deep debates on the ideas and controversies at the heart of ML research.
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#5Practical AI
Practical AI LLC
Applying machine learning in the real world — tools, MLOps, and production lessons.
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#6Data Skeptic
Kyle Polich
Kyle Polich explains data science and ML concepts clearly, with skepticism and rigor.
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#7The Gradient Podcast
Daniel Bashir
In-depth interviews with researchers across the breadth of modern AI and ML.
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#8Talking Machines
Tote Bag Productions
Conversations that make machine learning research accessible without dumbing it down.
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#9Latent Space: The AI Engineer Podcast
Latent.Space
For engineers actually shipping ML in production, Latent Space is the consensus pick — weekly technical interviews with senior engineers and researchers from OpenAI, Anthropic, Databricks, and Meta on agents, infrastructure, and applied models. Start with "Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks" (June 24, 2026) — with the creators of Apache Spark and MLflow.
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#10Super Data Science: ML & AI Podcast with Jon Krohn
Jon Krohn
Jon Krohn's long-running, near-daily show is the most practitioner-focused option on this list, covering the ML and data-science career, tooling, and techniques with working data scientists — over a thousand episodes deep. Start with "1004: Recursive Self-Improvement" (June 26, 2026).
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#11The Cognitive Revolution
Erik Torenberg, Nathan Labenz
Hosted by AI builder Nathan Labenz, the show keeps technical and business leaders current with in-depth interviews of the researchers, founders, and engineers shipping frontier models — one of the fastest-publishing serious AI shows going. Start with "Intelligence on the Edge: Liquid AI's Ramin Hasani on the Search for Device-Native Foundation Models" (July 4, 2026) — with the liquid-neural-network researcher.
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#12Dwarkesh Podcast
Dwarkesh Patel
Dwarkesh Patel's unusually well-prepared long-form interviews with leading ML researchers — on scaling laws, reinforcement learning, and AGI timelines — have become required listening in the field, and every episode ships with a full transcript. Start with "Grant Sanderson - AI and the future of math" (June 30, 2026) — with the creator of 3Blue1Brown.
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Listen to all 12 in one place
Free core listening with no app-inserted ads, limited offline listening, and optional AI summaries from Podcast Brain — all in The Podcast App.
Sources and further reading
- The TWIML AI PodcastOfficial show page — Sam Charrington's TWIML AI Podcast, technical ML/AI interviews.
- Gradient Dissent (Weights & Biases)Official Weights & Biases podcast page for Gradient Dissent, hosted by Lukas Biewald.
- The Robot Brains PodcastOfficial Acast show page — Pieter Abbeel interviews AI and robotics researchers.
- Machine Learning Street Talk (MLST)Official site for MLST, deep technical AI/ML debates hosted by Tim Scarfe.
- Practical AIOfficial Changelog Media site for Practical AI — applied ML, MLOps, production lessons.
- Data SkepticOfficial site for Kyle Polich's Data Skeptic, critical-thinking take on data science and ML.
- The Gradient PodcastOfficial podcast page — Daniel Bashir's in-depth AI/ML researcher interviews.
- Talking MachinesOfficial site for Talking Machines, machine learning conversations by Katherine Gorman and Neil Lawrence.
- Latent Space: The AI Engineer PodcastOfficial site — weekly technical interviews for engineers shipping ML in production.
- Super Data Science PodcastOfficial page for Jon Krohn's near-daily ML & data-science practitioner show.
- The Cognitive RevolutionOfficial site — Nathan Labenz's interviews with frontier-model researchers and builders.
- Dwarkesh PodcastOfficial site — Dwarkesh Patel's long-form interviews on AI scaling, RL, and AGI timelines.
- Machine learning — WikipediaReference overview of the machine learning field, the genre's core subject.
- Artificial intelligence — WikipediaReference overview of AI, the broader field these shows cover.
- Deep learning — WikipediaReference overview of deep learning, central to modern ML podcast topics.
- arXiv Machine Learning (cs.LG)The primary preprint archive for ML research these podcasts discuss.
- Papers with CodeReputable hub linking ML papers to code and benchmarks — high-value for practitioners.
- NeurIPSThe leading machine learning research conference, frequently referenced by these shows.
- The Gradient (magazine)Respected AI/ML publication founded at the Stanford AI Lab — journalistic genre coverage.
- The Ambies — Awards for Excellence in AudioPodcast Academy's award body recognizing excellence across podcasting.
- The Podcast AcademyMembership organization behind the Ambies, advancing the podcasting industry.
- arXivopen-access research preprint server
- Stanford HAIStanford Institute for Human-Centered AI
- MIT Technology Reviewauthoritative emerging-tech journalism
- Khan Academyfree education across subjects
Frequently Asked Questions
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For research and engineering both, start with The TWIML AI Podcast and Machine Learning Street Talk for depth, Latent Space for applied AI engineering, and Super Data Science for the data-science career and toolchain. For frontier research interviews, add the Dwarkesh Podcast and The Cognitive Revolution. Every show here offers free core listening in The Podcast App.
If you write ML code for a living, Latent Space is the consensus pick for applied AI engineering and agents, while Practical AI and Gradient Dissent focus on MLOps and getting models into production. Super Data Science covers tooling and career, and Data Skeptic keeps you rigorous on fundamentals. Follow a couple in The Podcast App for new-episode alerts as tools change.
The shows gaining the most ground in 2026 are the frontier-research interviews: the Dwarkesh Podcast, known for exceptionally well-prepared long-form conversations and full transcripts, and Nathan Labenz's The Cognitive Revolution, one of the fastest-publishing serious AI shows. On the applied side, Latent Space keeps setting the agenda for AI engineers. All three are free to follow with core listening included.
Every show on this page is available in The Podcast App with free core listening and no app-inserted ads. Download long technical interviews for offline listening, follow your favorites for new-episode notifications, and use the charts and personalized picks to surface new machine-learning and AI-engineering shows as the field moves.
Mastering Machine Learning: Your Essential Podcast Companion
The field of machine learning is evolving at an incredible pace, making it challenging yet crucial to stay updated with the latest research, breakthroughs, and industry applications. Podcasts offer an unparalleled way to absorb complex information, hear from leading experts, and gain new perspectives while on the go. Whether you are a seasoned data scientist, an aspiring ML engineer, or simply curious about artificial intelligence, integrating machine learning podcasts into your learning routine can significantly sharpen your skills and broaden your understanding. They provide a flexible and accessible format for continuous professional development, allowing you to transform commute times or daily chores into valuable learning opportunities.
Choosing the right machine learning podcasts can be overwhelming given the vast array of options. Look for shows that feature in-depth interviews with researchers, cover practical case studies, or break down intricate algorithms into digestible segments. Consider podcasts that discuss both the theoretical underpinnings and the real-world implications of ML, including ethical considerations and future trends. A well-curated selection will not only keep you informed but also inspire new ideas and approaches in your own work. Prioritize content that aligns with your current learning objectives, whether that is mastering deep learning, understanding reinforcement learning, or exploring the business side of AI.
The Podcast App is designed to elevate your machine learning podcast experience, making it easier than ever to learn and retain complex information. Our innovative Podcast Brain can search eligible transcript-backed moments from your listening history. This is particularly invaluable for machine learning topics, where clarifying concepts quickly can accelerate your learning curve. Furthermore, The Podcast App provides a listening experience with no app-inserted ads, ensuring uninterrupted focus on intricate discussions. You can also download episodes for offline listening, adjust variable playback speeds to match your comprehension, and seamlessly integrate with CarPlay for convenient access during your travels.
Beyond its powerful AI capabilities, The Podcast App offers a suite of features tailored for serious learners. Enjoy crystal-clear audio quality and a user-friendly interface that makes discovering new machine learning podcasts a breeze. with optional Premium for advanced features to access its core functionalities, it is available at no cost for both iOS and Android users, providing a premium listening experience without financial barriers. Embrace a smarter way to learn and stay ahead in the dynamic world of machine learning by leveraging The Podcast App’s comprehensive tools, designed to support your continuous growth and mastery of this transformative technology.
New in 2026
Machine-learning podcasting in 2026 split cleanly into two lanes, and both grew. On the practitioner side, the rise of agents and production LLMs made AI engineering its own discipline — Latent Space became the consensus pick for people shipping models, while Jon Krohn's Super Data Science passed a thousand episodes serving working data scientists. On the research side, long-form interview shows deepened: Dwarkesh Patel's conversations on scaling laws, reinforcement learning, and AGI timelines (each published with a full transcript) and Nathan Labenz's The Cognitive Revolution became go-to sources for tracking frontier work. The through-line was reasoning models and reinforcement learning displacing 2024's pure pre-training story — and a louder open-versus-closed debate, with figures like Databricks' Matei Zaharia arguing the open case on-mic.
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