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1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2Moderation: Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
1:01:14ENThe Model Eats the Scaffolding: How Google Plans to Ship Agents EverywhereModeration: Nathan LabenzThree years after the leaked “no moat” memo, DeepMind’s Gemini leads walk through 3.5 Flash, Omni, and the shared agent harness now running through Google’s products.
1:57:29ENFrontier vision models score 12.5%: Joseph Nelson on the real waterline of computer visionModeration: Nathan LabenzThe Roboflow CEO tells Nathan Labenz why vision still lags language, how to distill SAM 3 into an edge model for Wimbledon, and why the United States has almost never led open-source vision.
5:13ENTesting Meta’s SAM Audio: Isolating Voices and InstrumentsMatthew Berman · Forward FutureMatthew Berman demonstrates prompt-based sound separation and effects in a Meta-partnered video.
10:45ENWorld Labs Marble: Generate and Edit Navigable 3D WorldsMatthew Berman · Forward FutureMatthew Berman demos Marble’s multimodal inputs, scene editing and 3D navigation, including an attempt to recreate his office from one image.
42:20ENA Name Invented at 2:30 a.m. Put Gemini on Top of the App StoreModeration: Jacob EffronGoogle's Nicole Brichtova and Oliver Wang on Nano Banana, why image models got smart when language models did, and why a prompt still is not a finished product.
1:55:02ENA hundred experiments a day, and the valley of death in materialsModeration: Nathan LabenzRadical AI’s co-founders tell Nathan Labenz how a closed loop of frontier models and a self-driving lab is meant to collapse a forty-year materials cycle into less than a decade.
18:31ENTesting Nano Banana: Gemini 2.5 Flash Image EditingMatthew Berman · Forward FutureMatthew Berman tests character consistency, image edits, generation, visual sequences and common failure cases.
1:19:10ENA Robot-Arm Shot That Took Months Now Lives in a PromptModeration: Nathan LabenzLuma Labs’ Amit Jain and Jiaming Song on Ray 2, few-shot camera concepts, and why they think video models sit on the path to multimodal AGI.
1:43:54ENA Year to Grow a Brain Organoid, an Hour to Simulate ItModeration: Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.
3:53:49ENWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4oModeration: Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel BoringModeration: Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.
55:16ENGemini’s API Grew 14× in Six Months. Google’s PMs Explain the Catch-Up.Moderation: Nathan LabenzLogan Kilpatrick and Shrestha Basu Mallick walk through search grounding, Gemini Flash’s price-latency quadrant, and why a near-tied leaderboard still leaves Google third in most developers’ queues.
54:45ENA Few Megabytes of Doom and a Few Gigabytes of Model: Why Runway Bets on GeneralizationModeration: Nathan LabenzCTO Anastasis Germanidis tells The Cognitive Revolution why video is a fuller record of the world than text, why physics shows up without being programmed in, and how a small lab competes with unlimited compute.
2:04:15ENA parrot cannot paraphrase — and Claude cannot be talked into harmModeration: Nathan LabenzRobert Wright of the Nonzero podcast interviews Nathan Labenz on whether large language models understand anything, what Anthropic’s 10 million features actually show, and why open weights collide with U.S.–China policy.
1:16:22ENHe Spent 20 Hours Crafting a Prompt. DSPy Beat Him AnywayModeration: Nathan LabenzSander Schulhoff walks through The Prompt Report — a 78-page survey of what actually works when you prompt large language models.
1:37:07ENA Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.Moderation: Nathan LabenzGoogle researchers Vivek Natarajan and Khaled Saab walk Nathan Labenz through five medical-AI papers, from radiology reports to an AI doctor that still has to earn trust.
1:10:07ENSame Intelligence, 1% of the Price: Logan Kilpatrick on Gemini FlashModeration: Nathan LabenzA former OpenAI developer-relations lead, now the product manager for Google AI Studio, walks through what Gemini 1.5 Flash actually changes for builders.
3:04:52ENDoctors Chose AI on Eight of Nine Dimensions: A GPT-4 Red-Teamer's Scouting ReportModeration: Nathan LabenzNathan Labenz tells 80,000 Hours what late-2023 systems can already do, which thresholds still matter, and why a polarized policy fight is a gift to heavy-handed regulation.
16:28ENTesting Reka Core: Multimodal Benchmarks, Coding and ReasoningMatthew Berman · Forward FutureMatthew Berman reviews Reka’s reported model comparisons and tests Core on code, logic and image understanding.
1:34:11ENFrom forty hours in a scanner to one: reconstructing what you see from a shared brain spaceModeration: Nathan LabenzPaul Scotti explains how MindEye2 maps a new person's fMRI into CLIP with an hour of data, and why a linear layer plus better image generators changed the cost of reading minds.
1:01:53ENCompanion Apps Open Twice as Often as TikTok. a16z Only Funds Weird but WorkingModeration: Nathan Labenza16z consumer partners Anish Acharya and Justine Moore walk Nathan Labenz through their Abundance Agenda for AI-native consumer apps.
1:21:28ENThe Prompt Is a Bug: Suhail Doshi’s Bet on Control Over PixelsModeration: Nathan LabenzThe Mixpanel founder tells Nathan Labenz how a cloud browser, a canceled tweet, and a Thursday weight drop shaped Playground AI’s bet on images.
1:17:20ENHume wants well-being in the objective function, measured 53 emotions at a timeModeration: Nathan LabenzAlan Cowen tells Nathan Labenz how Hume AI reads face, voice, and language, sells custom models at $1.66 an hour, and wants long-horizon well-being to override every other AI goal.
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