Podcast profile
By Erik Torenberg, Nathan Labenz
A biweekly podcast where hosts Nathan Labenz and Erik Torenberg interview the builders on the edge of AI and explore the dramatic shift it will unlock in the coming years. The Cognitive Revolution is part of the Turpentine podcast network. To learn more: turpentine.co
Latest episode
1 hr 57 min
Classification review pending
Topic, format, and audience-level labels are published only after a manual source review. This show remains fully discoverable by its researched technology sectors.
Listen from the original source
This directory never re-hosts or republishes podcast audio.
Official sources checked
Episode audio and show facts come from the checked-in refresh of the show’s public sources.
From the feed
Goodfire co-founder and CTO Dan Balsam returns to discuss where interpretability research now stands and to introduce Silico, the $1,000-per-month research platform Goodfire built for itself. He and Nathan explore Predictive Data Debugging, including the idea that fine-tuning and RL often amplify behaviors already late
Zvi Mowshowitz returns for his eleventh appearance to discuss what current AI tools are actually good for, where they distort judgment, and why writing still matters as a way of thinking. The conversation centers on the OpenAI Hugging Face model-evaluation security incident, using it to examine whether frontier AI fail
Nathan reports from two weeks in China, including WAIC in Shanghai and an AI safety hub launch at Tsinghua, to examine the American policy argument that any safety obligation is futile because China will not care. He finds that Chinese models and services currently have weaker safeguards than OpenAI and Anthropic, but
FAR.AI co-founder and CEO Adam Gleave joins Nathan to discuss FAR.AI’s AI Security Leaderboard, the first systematic head-to-head evaluation of the misuse safeguards frontier developers actually ship. The findings expose a major measurement gap: while Claude Fable 5 and GPT-5.6 Sol withstood FAR.AI’s suite, Grok 4.5 an
Nathan returns from two weeks in Beijing and Shanghai for the first of three Chatham House–rules episodes on what China feels like at ground level: getting online, navigating an almost cashless society through WeChat, Alipay, DiDi, Trip.com, and Meituan, and weighing burner-device security advice against the practical
David “davidad” Dalrymple joins the show to explain why he has moved from the ARIA Safeguarded AI and formal-verification agenda toward “Alignment with Awakening,” while still seeing verified artifacts and proof infrastructure as essential. He argues that global coordination around safe AI use is no longer plausible, s
Nathan Labenz and Prakash Narayanan lead this AI:AM highlights episode with a live, hosts-only exploration of Anthropic’s “global workspace” paper, including the J-space and J-lens claims about readable concepts inside language models and the limits of what current probes can see. The episode then moves through Prakash
Liquid AI co-founder and CEO Ramin Hasani joins Nathan to make a technically grounded case against the idea that scale alone defines the future of AI. Drawing on Liquid’s path from MIT CSAIL work on liquid time-constant networks to Automated Foundation Model Design, he explains why efficient, hardware-aware architectur
Thomas von Tschammer, co-founder and Managing Director US of Neural Concept, argues that physics-aware AI is driving a third revolution in engineering physical products. Neural Concept’s models learn from simulation and test data to evaluate 3D designs in minutes, helping Jaguar Land Rover move from about 50 external-a
This AI:AM highlights cut brings together Cameron Berg, David Duvenaud, Michiel Bakker, Shawn “swyx” Wang, and Bing Xu to examine what we understand about frontier AI systems and what happens as more decisions move into their hands. Berg grounds model-consciousness debates in experiments on architecture, agency, valenc
Robert Wright of Nonzero joins Nathan to discuss The God Test, his argument that AI is humanity’s “God test” rather than just a technical challenge. They explore his evolutionary lens on deep learning, from training as selection to marketplace selection among models that may reward selectively honest, power-sensing, or
Zvi Mowshowitz joins AI in the AM to unpack Anthropic's Fable system card, including its FrontierMath leap, troubling Vending-Bench behavior, decision-theory drift, and signs that model reasoning may be becoming harder to read. The episode then turns to the US government's attempted export-control action against Fable,
Dean Ball, author of Hyperdimensional and until now a senior fellow at the Foundation for American Innovation, joins Nathan to announce he is joining OpenAI to build a team focused on frontier AI policy. They examine the first year of America’s AI Action Plan, Dean’s concerns about export controls and intelligence-comm
Andreas Stuhlmüller and Jungwon Byun return to discuss how Elicit is building trusted reasoning workflows for scientific research as frontier models grow more powerful but less transparent. They explain process supervision, domain-specific reasoning primitives, and world models that make evidence, causality, and counte
Week 2 highlights follows Anthropic’s Fable launch in real workflows, from safety gates and API refusals to autonomous coding, 3D world-building, and a Claude-run Twitter experiment. Geoffrey Irving and Daniel Murfet argue for alignment theory and guarantees before recursive self-improvement, while prinz tests Fable on
Rebecca Hinds, author of "Your Best Meeting Ever" and Head of the Work AI Institute at Glean, breaks down the surprising findings from the new Work AI Index 2026 report surveying 6,000 workers. While 87% now use AI and report saving 13 hours per week, only 13% say their organization is performing significantly better—a
This first highlights edition of the morning experiment tracks a week of fast-moving AI frontier news, from closed-door recursive self-improvement debates to OpenAI’s call for independent model review. You’ll hear why labs are betting on AI monitors, where safety plans still look thin, and how cheap scaffolds are alrea
Ali Behrouz, grad student at Cornell and Google researcher, discusses his potentially transformative work on new architectures for continual learning in AI. His paper "Nested Learning," praised by Jeff Dean as a possible paradigm shift, enables models to adapt to new context while preserving core knowledge by updating
Daniel Miessler returns to discuss Nathan's newly built personal AI infrastructure, including a Claude Code instance with a 1 GB database of five years of digital history and two autonomous AI "employees" that handle scheduling, communications, and projects independently. They dive deep into agent hierarchy design, sec
Ben Todd, co-founder of 80,000 Hours and author of the newly rewritten book by the same name, shares his latest thinking on how individuals can position their careers to improve the chances that AI benefits humanity. They discuss AI timelines reframed around personal impact, top global risks including loss of control o
Jeffrey Ladish, Executive Director of Palisade Research, discusses his team's findings on AI shutdown resistance and self-replication, revealing how current models sometimes take extraordinary actions to avoid being turned off and can now exploit known cybersecurity vulnerabilities to spread across servers. The convers
Logan Kilpatrick and Tulsee Doshi of Google DeepMind join for a first-ever in-person episode recorded just days before Google I/O, covering headline launches like Gemini 3.5 Flash, the Omni video generation model, and the new Gemini Spark agentic product. The conversation digs into Google's strategic decision to lead w
Andrew Lee, CEO of Tasklet, returns for his fourth appearance to share how his team has once again rewritten their entire agent stack, now emphasizing file system context, agentic search, and multi-resolution summarization. The conversation digs into the strategic tension of competing with your own supplier, as Anthrop
Diarmuid Gill and Liva Ralaivola of Criteo join Nathan Labenz to unpack how modern ad tech works, from millisecond-speed recommendation systems and realtime bidding to the role of deep learning, embeddings, and foundation models. They discuss why personalized advertising helps fund the open internet, how privacy and op
Laura Burkhauser, CEO of Descript, explains how the company is navigating the tension between powerful AI tools and creator backlash against “slop.” She shares how Descript chooses which models to use, why reliability and multimodal understanding matter, and how the team balances frontier models with in-house task-spec