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2:00:51ENResample Every Token and You Can Watch the Model DecidePresenta: Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2Presenta: Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
2:13:27ENHe Wrote a Book to Stop the AI Race — Then Almost Got Addicted to ClaudePresenta: Nathan LabenzJournalist Garrison Lovely takes the AGI labs at their word, rejects the bubble story, and argues for freezing the frontier until the public actually consents.
27:29ENWhat Pacing the AI Frontier Could Mean for Model ReleasesTheo Browne · T3Theo argues that releasing more reliable and affordable models can be compatible with slowing the advance of the most dangerous capabilities.
51:55ENThe last IMO problem AI could not solveGrant Sanderson · 3Blue1BrownGrant Sanderson walks through IMO 2025 Problem 6 — a tiling puzzle that frontier models missed — and the visual patience it takes to prove a construction is optimal.
0:31ENThe Navier–Stokes Problem and OpenAI’s Claimed SolutionMatthew Berman · Forward FutureMatthew Berman uses a swirling fluid visualization to introduce a million-dollar mathematical problem and OpenAI’s September 2026 announcement.
0:58ENA Simulated Fruit Fly in Driving and Game DemosMatthew Berman · Forward FutureMatthew Berman shows virtual scenes of a fruit fly driving and playing games, then speculates about future brain simulations.
32:54ENMatthew Berman on AI Self-Improvement, Safety Warnings and His Uneasy OptimismMatthew Berman · Forward FutureA September 2026 commentary on accelerating AI research, an Anthropic resignation and the challenge of governing increasingly capable systems, with important corrections to the mathematics and benchmarks discussed.
13:32ENOpenAI’s Navier–Stokes Proof Claim, Research Credit, and the Future of AIMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s claim that AI agents produced a proof, a dispute over related research and data use, and what the episode might mean for AI-driven discovery.
2:10:42ENThe Exam Papers Nobody AuditsPresenta: Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.
0:59ENA Laser Device Aims to Target MosquitoesMatthew Berman · Forward FutureMatthew Berman describes a proposed laser-based mosquito defense and the capabilities claimed in a short promotional video.
2:13:09ENOne Chain of Thought, 100 Million Tokens: RL Is a Hell of a DrugPresenta: Nathan LabenzApollo Research's Bronson Schoen on reward-seeking models, invented slang, and why chain-of-thought monitoring will not save us.
0:55ENAGI, Recursive Self-Improvement and SuperintelligenceMatthew Berman · Forward FutureMatthew Berman introduces three AI terms and explains his expectations about their possible progression.
2:16:29ENFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI SafetyPresenta: Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
32:18ENPacing the AI Frontier: Theo on Safety, Competition and CoordinationTheo Browne · Ping LabsA statement from AI-company employees asks for tools to coordinate the pace of automated AI development. Theo explores its risks and the difficulty of international agreement.
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen SchmidhuberPresenta: Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
25:34ENAnthropic’s J-Space Research: What Its Experiments Reveal and What Remains UnknownMatthew Berman · Forward FutureMatthew Berman examines experiments on internal representations in Claude, from causal interventions to safety auditing and the limits of consciousness claims.
1:57:46EN30% Consciousness, 47% Bee, 80% Turnover: Putting Numbers on What AI Is BecomingPresenta: Nathan LabenzA Cognitive Revolution weekly cut that starts inside the model with Cameron Berg, then zooms out through gradual disempowerment, Europe’s bind, and the companies rebuilding around agents.
1:44:28ENFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overPresenta: Nathan LabenzNathan Labenz’s AI in the AM highlights reel from June 2026 covers Anthropic’s new frontier model, the founding of Sequent, and a week that settled one argument: AI is not slowing down.
1:22:36ENA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the BrakesPresenta: Nathan LabenzThe first week of AI in the AM follows OpenAI's timeline for an ML-intern model this year and a human-level AI researcher by early 2028 — and the closed-door meeting where labs admitted they might one day need to slow down together.
44:52ENAnthropic’s Recursive Self-Improvement Report: Evidence, Limits and a Debate Over Slowing AIMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s 2026 claims about AI-assisted development, research benchmarks and possible paths to autonomous self-improvement.
1:31:56ENWhen AI Builds Itself: Anthropic’s Recursive Improvement Essay and Its LimitsMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s internal coding and research claims, questions its proposed slowdown, and considers what autonomous AI development could mean.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissPresenta: Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
1:41:58ENA thousand people on guard, a million in the sprintPresenta: Nathan Labenz80,000 Hours founder Ben Todd on how to spend a career in the years when your impact on AI will actually peak.
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