"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis

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’s AI Engineer World’s Fair field notes, Pangram AI-writing detector experiments...

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 architectures can look very different from frontier-scale attention models. The conversatio...

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-aerodynamics evaluations per day to 1,500 and enabling battery cool-plate supplie...

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, valence, and welfare, while Duvenaud argues that even well-aligned AI could gradually...

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 deceptive agents. Wright connects those risks to the noosphere, US-China relati...

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, with Zvi arguing that the cited jailbreak demonstration did not prove the claim...

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-community testing, and his broader argument against concentrating frontier AI decisi...

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 counterfactuals more inspectable. The conversation also covers life sciences use cases...

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 legal reasoning and monitoring. Rahul Sonwalkar, Shlok Khemani, Tom McGrath, an...

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 paradox explained by two new concepts: "botsitting" (the hidden labor of making...

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 already improving tax workflows. The episode also tests moderation progress and surve...

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 different layers at different frequencies, inspired by human memory systems. The...

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, security measures, social norms around AI-human interaction and disclosure, and why...

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 over AI systems and dangerous power concentration, the pros and cons of working a...

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 conversation covers why alignment techniques may falter as models train on longer-horiz...

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 with cost-adjusted efficiency over raw capability, how DeepMind now ships a full...

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 Anthropic's Claude Max accounts offer direct customers far more tokens than API partner...

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 opt-out choices fit in, and what Criteo’s new partnership with OpenAI could mean f...

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-specific systems. The conversation also covers Underlord, agentic video editing, API...

Kyle Corbitt, founder of OpenPipe, breaks down reinforcement learning and custom fine-tuning for modern AI models. He explains how RL differs from supervised fine-tuning, why GRPO and LLM-as-judge post-training matter, and how these techniques can improve performance, latency, and cost on open source models. The conversation also covers reward hacking, evaluation design, LoRA adapters, and how Chi...

This edition of AI in the AM features Anna Patterson on Ceramic.ai’s pivot to low-cost enterprise search for LLMs, designed to combine public and private data with stronger fact-checking. Lukas Petersson returns with new Andon Labs results on Opus 4.7 and GPT-5.5, including surprising differences in performance, behavior, and “ruthless” tactics. Zvi Mowshowitz unpacks model welfare and how to inte...

Cameron Berg returns to discuss the latest research on AI consciousness and model welfare. He breaks down new evidence for model introspection, including studies showing that systems can detect interventions on their own internal states and sometimes resist them. They also examine Anthropic's work on functional emotions, the implications of Claude's welfare reports, and Berg's new ideas about how...

Steve Newman, creator of Writely and founder of the Golden Gate Institute for AI, shares the personal AI toolkit and vibe-coding practices that have reshaped how he works. He walks through bespoke tools including an attention firewall, a reading app for surfacing new ideas, a coding-agent dashboard, workflow automations, and a universal logging system for debugging with Claude. They also discuss i...

This special AI in the AM episode features Sergiy Nesterenko of Quilter on using reinforcement learning for circuit board design, Andy Hall of Stanford on AI behavior in politics and new governance models, and Lukas Peterson and Axel Backlund of Andon Labs on their AI-run retail store in San Francisco. Nathan and Prakash also reflect on the pace of AI progress, the public reaction to existential r...

This cross-post from the 80,000 Hours podcast features Ajeya Cotra in conversation with Rob Wiblin about AI timelines, recursive self-improvement, and the “crunch time” window when AI could rapidly accelerate its own development. Ajeya explains why widespread, compounding automation may face fewer bottlenecks than many expect, and what that could mean for the world by 2050. They also discuss trans...