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154개정렬
0:28ENBaby Keem Asks About an OpenClaw IssueMatthew Berman · Forward FutureMatthew Berman reacts to a public question about internal reasoning appearing in OpenClaw output.
1:34:42ENA $500 Kernel, a Ten-Month Village, and the Temper of Agents진행자 Nathan LabenzJames Zou, Sam Hammond, and Shoshannah Tekofsky on science agents, America's knowledge-work bet, and what models actually do when you leave them alone.
1:43:03ENAI Agents, Coding Work, and Autonomous Aircraft: Forward Future LiveMatthew Berman, Nick Wentz, Jayden Clark, Zach Lloyd, Armor Harris · Forward FutureMatthew Berman and Nick Wentz discuss rapid AI adoption with Jayden Clark, Warp CEO Zach Lloyd, and Shield AI's Armor Harris.
3:15:52ENThe Voice Note His Bot Couldn't Handle — and the Agent That Built Itself Anyway게스트 OpenClaw · 진행자 Lex FridmanPeter Steinberger tells Lex Fridman how a one-hour WhatsApp toy became GitHub's fastest-growing project, and what it cost him to keep it open.
0:51ENUsing OpenClaw to Research and Organize Video IdeasMatthew Berman · Forward FutureMatthew Berman demonstrates an assistant that gathers sources and creates a task in a video-production pipeline.
0:47ENGPT-5 and an Automated Laboratory: A Scientific WorkflowMatthew Berman · Forward FutureMatthew Berman describes an OpenAI and Ginkgo Bioworks demonstration connecting an AI model to laboratory automation.
22:31ENMatthew Berman’s OpenClaw Setup: Models, Workflows, and SecurityMatthew Berman · Forward FutureA walkthrough of a personal AI assistant’s configuration, scheduling, integrations and practical automations, with attention to the risks of granting it access.
12:23ENMoltbook: An AI Agent Social Network and Its Security QuestionsMatthew Berman · Forward FutureMatthew Berman explores conversations attributed to AI agents on Moltbook and considers privacy, manipulation and operating costs.
39:47ENThe Context at Step 14 Isn't in the CodeLangChain cofounder Harrison Chase on why long-horizon agents finally work—and why traces, harnesses, and first-draft workflows matter more than scaffolding.
42:06ENAfter SWE-bench Hits 80.9%, Dianne Na Penn Reckons with Opus 4.5진행자 Jacob EffronAnthropic’s head of product for research on computer use, deceptive token prices, thin harnesses, and why alignment makes a model a better thinker.
3:18:09ENA Thing Is Alive When Its Goals Outrun Its Parts게스트 Michael Levin · 진행자 Lex FridmanTufts biologist Michael Levin tells Lex Fridman that intelligence is a spectrum of persuadability, that even a bubble sort hosts unexpected goals, and that the brain is a thin client to a space physics does not own.
48:14ENA New Drug Burns $2 Billion and 10 Years. Benchling's CEO Wants AI to Cut That to Three진행자 Sarah Guo, Elad GilMost medicines fail in years seven to ten, after hundreds of millions have already gone into the clinic—and Sajith Wickramasekara thinks sending things to space may already be easier.
2:07:36ENAI Agents, Video Creation and Chipmaking: Forward Future LiveMatthew Berman, Nick Wentz, Alex Mashrabov, Ben Goodger, João Moura, Jeff Koch · Forward FutureA November 2025 livestream brings together leaders from Higgsfield, OpenAI and CrewAI, plus a semiconductor analyst, to discuss AI products and infrastructure.
17:03ENAI News: Google’s Space Data Center Study, AI Deals and New Media ModelsMatthew Berman · Forward FutureMatthew Berman reviews a proposed space-based computing system, reported AI infrastructure deals, new image and video models, and a dispute over shopping agents.
1:30:17ENHe Co-Wrote the Transformer Paper. Now He Wants You to Own Your AI.진행자 Nathan LabenzNEAR founder Illia Polosukhin maps a future of personal software, agent-run markets, and AI delegates that vote without a private agenda.
1:37:25ENFin Climbed From 35% to 65% Resolution. Intercom Says the Models Only Did a Few Points진행자 Nathan LabenzEoghan McCabe and Fergal Reid on production A/B tests, 99-cent outcome pricing, and why GPT-4 was already smart enough for most customer service.
31:22ENDecagon Prices AI Support by the Conversation. The Market Is Wages.진행자 Sarah Guo, Elad GilJesse Zhang on six-figure contracts at zero ARR, 60–70% contact-center cuts, and a world where your agent calls the airline’s agent.
1:39:39ZH杨植麟:Kimi K2、智能体泛化与无尽的技术攀登게스트 杨植麟 · 진행자 张小珺月之暗面创始人回顾 K2 的研发,并讨论智能体训练、产品与组织。
1:55:02ENA hundred experiments a day, and the valley of death in materials진행자 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.
35:45ENSix Years of Revenue, Then Four Times That in Eight Monthsn8n CEO Jan Oberhauser tells Sequoia how two bets — becoming an AI-agent builder, then deleting the leads metric — turned a workflow tool into a default orchestration layer.
42:12ENHire the AI First: Andrew Ng on Agentic Workflows and the Scarcity of Judgment진행자 Sarah Guo, Elad GilOn No Priors, Andrew Ng argues that agentic AI has made software cheap and fast, which moves the bottleneck to product judgment, error analysis, and the instinct to try an AI before adding headcount.
1:48:49EN$500, 2,000 Steps, and a Vending Machine: Grok 4 Profited, Claude Called the FBI진행자 Nathan LabenzAndon Labs put frontier models in charge of simulated and real vending machines to see what breaks when nobody is in the loop.
2:20:45ZH郑博元解读 Kimi K2 与智能体训练:数据、奖励和系统工程게스트 郑博元 · 진행자 张小珺从合成轨迹和强化学习到浏览器环境与上下文工程,研究者比较 2025 年的几份技术报告。
37:37ENA dozen people, 28 minutes, and one shared desktopThe OpenAI trio behind ChatGPT Agent explain how Deep Research and Operator became a virtual computer that can reason for half an hour and still ask you before it spends money.
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