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1:23:09ENThe Right Size of an AI Task Is Whatever You Can CheckPresenta: Nathan LabenzElicit founders Andreas Stuhlmüller and Jungwon Byun walk through how a twelve-person research assistant cut summary hallucinations from 1.5 to 0.5, ships about every week and a half, and treats task decomposition as the way to spend more compute without a black box.
1:20:44ENSeeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 DaysPresenta: Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.
1:29:21EN2,700 AI Authors, No Consensus: Even Odds of HLMI in 2047, 5% ExtinctionPresenta: Nathan LabenzKatja Grace of AI Impacts walks Nathan Labenz through a survey of researchers who published in top venues in 2022—and why the field’s only real consensus is uncertainty plus more safety work.
22:17ENQ* Rumors, Energy-Based Models, and Research on ReasoningMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines an anonymous, unverified account of Q* and compares its ideas with published research on teaching language models to reason.
18:42ENRobot Demonstrations in 2024: 1X, NVIDIA, Spot and BeyondMatthew Berman · Forward FutureMatthew Berman surveys humanoid, quadruped, drone and defense robotics, distinguishing company demonstrations from general-purpose autonomy.
52:06ENYann LeCun on World Models, Open AI and the Path to Advanced IntelligenceMatthew Berman, Yann Lecun, Lex Fridman · Forward FutureMatthew Berman reacts to excerpts from LeCun’s 2024 conversation with Lex Fridman, covering language models, JEPA, robotics, AI safety and economic incentives.
12:34ENFigure 01 and the Path Toward More Capable RobotsMatthew Berman, Lex Fridman, Yann Lecun · Forward FutureMatthew Berman surveys humanoid and other robotics demonstrations, then shares Yann LeCun’s view on the work still needed for general-purpose robots.
21:16ENArtPrompt: What a 2024 Study Found About Visual Text and Model SafetyMatthew Berman · Forward FutureMatthew Berman reviews an ASCII-art recognition benchmark and reports mixed results from his own informal tests.
2:47:17ENIf You Want Human-Level AI, Abandon Generative ModelsInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.
Google Gives You 33 Million Results. Exa Wants 54.Presenta: Nathan LabenzWill Bryk, CEO of Exa, tells Nathan Labenz why search and research are different jobs, and why an AI librarian for the web has to be neural from the first filter.
21:41ENGoogle Genie and the Idea of Generated Interactive WorldsMatthew Berman · Forward FutureMatthew Berman explores early world-model research, generated media and simulated agents while imagining a future of personalized games.
30:39ENNVIDIA’s GEAR Research, Gemini 1.5 and Fast AI InferenceMatthew Berman · Forward FutureMatthew Berman reviews embodied-agent research and a February 2024 set of AI releases and demonstrations.
15:56ENSora, World Models, and the Speculation Around Simulated RealityMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s early Sora videos and researchers’ ideas about learned physics, future games, and simulation theory.
1:25:09ENTwo-Headed Worms, Regenerated Legs, and a Sort That Learned to WaitPresenta: Nathan LabenzTufts biologist Michael Levin tells Cognitive Revolution why anatomy is rewritable software, and why he stopped a paper that might have made AI more alive.
21:00ENJim Fan's Foundation Agent Vision: Skills, Robot Bodies, and SimulationMatthew Berman, Jim Fan · Forward FutureMatthew Berman examines research on Minecraft agents, varied robot bodies, and simulation as steps toward more general embodied AI.
35:22ENMatthew Berman’s Ten AI Predictions for 2024Matthew Berman, Mark Zuckerberg, Lex Fridman, Jaron Lanier, Joon Park, Elon Musk · Forward FutureAn early-2024 forecast covers model releases, robotics, agents, synthetic data and the risks of increasingly convincing bots.
3:53:04ENHe Red-Teamed GPT-4 and Got Cut Off. The Control Gap Is Still OpeningPresenta: Nathan LabenzNathan Labenz tells Rob Wiblin how an early look at GPT-4, a thin red-team program, and a year of OpenAI's public safety moves reshaped his view of the AGI race.
2:30:06ENTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home TurfPresenta: Nathan LabenzIn a solo emergency episode, Nathan Labenz argues that Albert Gu and Tri Dao's selective state space model is the first architecture since 2017 that deserves to share the Transformer’s throne.
19:37ENHow Rephrased Test Data Inflated a 13B Model’s Benchmark ScoresMatthew Berman · Forward FutureMatthew Berman examines a 2023 experiment showing how reworded benchmark questions can evade simple contamination checks and inflate model scores.
1:28:07ENThe AIs We're Most Afraid Of Don't Exist Yet — So She's Studying Amoebas and Firm BoundariesPresenta: Nathan LabenzNora Ammann of PIBBSS argues that intelligent behavior may share principles across brains, cells, markets, and future AI — and that we need those other systems because we cannot trial-and-error the ones that would be too powerful to get wrong.
1:22:59ENIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%Presenta: Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.
35:16ENWhat Was Known About Q* in 2023—and What Was SpeculationMatthew Berman, Sam Altman, Andrej Karpathy · Forward FutureMatthew Berman surveys rumors, reasoning papers and self-play analogies after OpenAI’s leadership crisis, with important limits on what was verified.
1:19:24ENA Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.Presenta: Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.
41:58ENReliability is the bottleneck. Autonomy is what would make AI feel alive.Presenta: Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.
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