筛选结果
46 篇排序
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2主持 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 Everywhere主持 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.
1:57:29EN → 简体中文前沿视觉模型得分 12.5%:Joseph Nelson 谈计算机视觉的真实水位线主持 Nathan LabenzRoboflow 的首席执行官向 Nathan Labenz 解释,视觉为何仍落后于语言,如何把 SAM 3 蒸馏成温布尔登可用的边缘模型,以及美国为何几乎从未在开源视觉上领先。
42:20ENA Name Invented at 2:30 a.m. Put Gemini on Top of the App Store主持 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 materials主持 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.
1:19:10ENA Robot-Arm Shot That Took Months Now Lives in a Prompt主持 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 It主持 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.
3:53:49EN → 简体中文数据只有十二分之一,一个开源视觉模型击败了 GPT-4o主持 Nathan LabenzVeratai 的 Will Hardman 带 Nathan Labenz 梳理了两年来的视觉语言模型(VLM),从 ViT 和 CLIP 讲到 InternVL、BLINK 和 Transfusion。
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel Boring主持 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.主持 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 Generalization主持 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 harm主持 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 Anyway主持 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.主持 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 Flash主持 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.
3:04:52EN → 简体中文医生在九个维度中有八个更青睐 AI:一位 GPT-4 红队测试者的侦察报告主持 Nathan LabenzNathan Labenz 在 80,000 Hours 播客上讲述 2023 年末的系统已经能做什么、哪些门槛仍然重要,以及两极化的政策之争为何反而成了强硬监管的礼物。
1:34:11ENFrom forty hours in a scanner to one: reconstructing what you see from a shared brain space主持 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 Working主持 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 Pixels主持 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 time主持 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.
1:19:24ENA Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.主持 Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.
1:36:39ENOpenAI’s $5 Million Bet: A 60-Person Team Wants GPT-4V to Give Cars Common Sense主持 Nathan LabenzGhost Autonomy cofounder John Hayes tells Cognitive Revolution why a multimodal model on the driving path could reset self-driving after two decades of DARPA-era stacks.
1:14:48ENDevDay Probably Created Thousands of Startups, Says OpenAI's Logan Kilpatrick主持 Nathan LabenzThe day after OpenAI's first developer conference, Dev Relations lead Logan Kilpatrick tells Nathan Labenz why thin wrappers were never companies, why agents were deliberately not shipped fully autonomous, and what $2 million custom models are for.
1:32:40ENThe Historian Who Taught GPT-3.5 to Beat GPT-4主持 Nathan LabenzMark Humphries on a kilometer of unread paper, fur-trade jargon that embeddings cannot see, and why cheap processing will force history to be rewritten.
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