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189 件並び順
2:00:51ENResample Every Token and You Can Watch the Model Decideホスト 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-2ホスト 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 Claudeホスト 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.
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.
2:10:42ENThe Exam Papers Nobody Auditsホスト 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 Drugホスト 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 Safetyホスト Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuberホスト 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.
1:57:46EN30% Consciousness, 47% Bee, 80% Turnover: Putting Numbers on What AI Is Becomingホスト 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 overホスト 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 Brakesホスト 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.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Missホスト 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 sprintホスト Nathan Labenz80,000 Hours founder Ben Todd on how to spend a career in the years when your impact on AI will actually peak.
1:21:56ENYann LeCun Left Meta Because LLMs Will Not Get You to Intelligenceホスト Jacob EffronThe Turing Award winner tells Jacob Effron why he spun AMI Labs out of Meta, why JEPA-style world models beat pixel generators, and why he thinks Hinton changed his mind in 2023.
1:03ENWhy EVE Online Is an Interesting Environment for AI ResearchMatthew Berman · Forward FutureMatthew Berman explains why the game's persistent economy and player alliances may offer a demanding test of long-term planning.
17:21ENDeepSeek V4, Model Efficiency and the US–China AI DebateMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s April 2026 V4 preview and argues that efficient open-weight models raise questions for American AI providers and policymakers.
3:36:29ENClaude Rated Its Own Welfare 4.49 — the First Time Any Version Crossed Neutralホスト Nathan LabenzCameron Berg returns to The Cognitive Revolution to survey six months of introspection, functional-emotion, and model-welfare research, plus a still-unpublished case that learning and feeling may be the same phenomenon.
3:10:49ENCrunch Time: Ajeya Cotra's Playbook for the Months Before Superintelligenceホスト Nathan LabenzA conversation on recursive self-improvement, public warning systems, and using each generation of AI to align and control the next.
58:46ENTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028ホスト Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
11:55ENA Simulated Fruit Fly Raises Questions About Brain EmulationMatthew Berman · Forward FutureMatthew Berman examines a connectome-based virtual fly and considers what it might mean for neuroscience, consciousness and simulation theory.
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