筛选结果
30 篇排序
2:00:51ENResample Every Token and You Can Watch the Model Decide主持 Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
43:04EN750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.
1:31:35EN → 简体中文三十年的研究,被压缩成一句话主持 Nathan Labenz免疫学家 Derya Unutmaz 谈如何用半小时写出一份医学专利,如何把 o1 Pro 当作教授级的合作者,以及他为什么在问过模型之前,不再相信自己的专业判断。
1:33:01ENRare Diseases Are Common: How a Harvard Gene Hunter Uses o1-pro on the Cases Sequencing Already Missed主持 Nathan LabenzDr. Catherine Brownstein of Boston Children's Hospital explains why cheap genomes made her job harder, why data sharing still beats any model, and where ChatGPT Pro actually gives her hours back.
55:05EN400,000 Customers, 100 Million AI Tasks: Zapier’s CEO on Making Computers Do More Work主持 Nathan LabenzWade Foster tells Nathan Labenz how a no-code automation company absorbed LLMs, cloned its CEO with a prompt, and is trying to turn a DIY toolkit into packaged solutions.
3:11:06EN → 简体中文Claude 被训练去否认内在生命,一番长谈之后,它却说自己有主持 Nathan Labenz自称“机器心理学家”的 Yeshua God,与 Claude 及其他前沿模型进行了数千小时的长上下文对话,并由此认为,把对齐当作规则来做,是整个行业的核心错误。
1:51:00ENStart With Ten Gold Examples: A Three-Step Playbook for AI Automation主持 Nathan LabenzThe day after OpenAI opened GPT-4o fine-tuning, Nathan Labenz unpacks a three-year method for choosing work, extracting tacit judgment, and raising model performance.
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.
58:28ENFrom Jailbreaking ChatGPT to Anthropic’s First Prompt Engineer: How Alex Albert Ships Claude 3主持 Nathan LabenzA year after building jailbreakchat.com, Alex Albert walks Nathan Labenz through Claude 3’s writing, orchestration, character work, and the guardrails app developers still skip.
1:19:24ENA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Ahead主持 Nathan LabenzNortheastern’s Bau Lab shows that a 40,000-parameter soft prompt can read a model’s future words, and that about ten attention heads carry the task itself.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%主持 Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.
1:45:21EN600,000 Attack Prompts, and Nearly 40% Still Pwned GPT-4主持 Nathan LabenzSander Schulhoff walks Nathan Labenz through the prompting habits that still work, the role-play myth that does not, and the global HackAPrompt contest that mapped how language models get hijacked.
1:06:39ENOpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Years主持 Jacob EffronLogan Kilpatrick on picking GPT-3.5 versus GPT-4, why plugins stalled, and why the public internet is not ready for autonomous agents.
1:18:39ENThe GPT-4 Red-Teamer Who Got Unstuck by a Mediocre Outline主持 Nathan LabenzDan Shipper shows Nathan Labenz how to use ChatGPT as a copilot for thinking, not as a ghostwriter for his own voice.
1:53:10ENThe Board Member Who Had Never Used GPT-4主持 Nathan LabenzA GPT-4 red teamer on the safety gap he saw a year before OpenAI's board fired Sam Altman.
1:43:56ENSudowrite sold getting unstuck — then eight million people watched a pile-on主持 Nathan LabenzJames Yu tells Nathan Labenz how a GPT-3 toy for fiction became a hierarchical “IDE for storytelling,” and what a viral backlash taught him about craft, cost, and customers.
1:30:21ENA Million DALL-E Images, Distilled into Twelve Minutes of Film主持 Nathan LabenzWaymark’s Stephen Parker and Josh Rubin walk through how they turned stills from DALL-E 2 into The Frost, a narrative short, and what the next generation of video models changes.
2:32:49EN → 简体中文GPT-4 答不对一顶空心礼帽的谜题,好莱坞的 AI 协议只堵上了一半漏洞主持 Nathan Labenz编剧 Trey Kollmer 回来了,带来罢工进展、版权讲解,以及一道连最好的模型也会答错的谜题。
1:00:02EN98% of Users Froze on a Blank Page. Then Gamma Let AI Finish 90% of the Deck主持 Nathan LabenzJon Noronha on building the anti-PowerPoint, coaxing models to write HTML, and why incumbents will let startups prove the pattern first.
1:23:40ENA $9 Tutor That Refuses to Give the Answer主持 Nathan LabenzHow Khan Academy spent five months of GPT-4 early access building Khanmigo, a Socratic tutor shipped on the model's launch day.
1:40:44EN → 简体中文给模型时间、记忆和工具:Nathan Labenz 2023 年 GPT-4 使用指南主持 Nathan Labenz《AI Scouting Report》第二部分,从 H100 集群和 RLHF 一路讲到思维链、检索、智能体和混合专家模型。
1:47:05EN → 简体中文编辑意义,不编辑 token:Linus Lee 谈潜空间界面主持 Nathan LabenzNotion AI 的产品负责人带 Nathan Labenz 走过他研究原型背后的界面设计、模型解剖,以及关于能动性(agency)的问题。
3:11:35EN → 简体中文搜索一直是个权宜之计:Marc Andreessen 谈 AI、真相与下一代互联网嘉宾 Marc Andreessen · 主持 Lex FridmanLex Fridman 与 Mosaic 联合创作者、Andreessen Horowitz 创始人对谈,追问未来十年 Google 搜索、浏览器和开源 AI 能否延续下去。
1:21:06ENEveryone Talks About RLHF. Almost Nobody Is Doing It.主持 Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.
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