絞り込み結果
269 件並び順
1:23:53ENGPT-4, 24 Hours Later: No Safety Locks, a Captcha Hire, and a U.S.–China Deadlockホスト Nathan LabenzA day after OpenAI shipped GPT-4, ChinaTalk sat a red teamer, a pessimist, and a policy researcher down to argue over capability, safety, and a race nobody can brake.
11:53ENTesting GPT-4 Against GPT-3.5 at LaunchMatthew Berman · Forward FutureMatthew Berman reviews OpenAI's March 2023 GPT-4 announcement and compares the models on scheduling, reasoning, safety and travel prompts.
1:13:06ENLockheed Martin's CTO on Autonomy, the Moon, and the Culture of Not Getting It Wrongゲスト Keoki Jackson · ホスト Lex FridmanKeoki Jackson tells Lex Fridman why going back to the Moon is the easy part—and why proving a learning system will still do the right thing is not.
1:45:49ENTrust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the Companyホスト Nathan LabenzAndreas Stuhlmüller and Jungwon Byun explain how Elicit keeps frontier models checkable for high-stakes science, and where they think AI reasoning is heading.
1:25:13ENCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a Teammateホスト Lenny RachitskyCodex product lead Alexander Embiricos explains the 20x growth, why every useful agent may need to write code, and why human review speed is the real bottleneck.
1:33:50ENEvals Are the New PRDs: Inside Anthropic's Research Product Teamホスト Lenny RachitskyDianne Penn, Anthropic's head of product for research and Labs, explains how the company found its identity, how her team turns user feedback into evals, and why human judgment still matters.
1:31:41ENThe Worst Model You'll Ever Use: Kevin Weil on Building Products at OpenAI's Paceゲスト Kevin Weil · ホスト Lenny RachitskyOpenAI's chief product officer explains how evals, light planning, fine-tuned model ensembles and a small PM team shape the way the company ships.
1:22:36ENStop Chasing AI News: Chip Huyen on What Actually Makes AI Products Betterゲスト Chip Huyen · ホスト Lenny RachitskyAuthor of AI Engineering walks through pre-training, post-training, RL, evals and RAG, then explains what separates companies that get value from AI from those that stall.
1:07:08ENIf the Model Is the Product, the Eval Is the PRD: Inside Mercor's Riseゲスト Brendan Foody · ホスト Lenny RachitskyMercor CEO Brendan Foody explains why AI labs will pay almost anything for expert-written evals, how his company grew from $1 million to a $400 million run rate in 16 months, and what that means for jobs and founders.
51:30ENLess Email, Better Thinking: Grammarly’s CEO on AI That Augments Communicationホスト Jacob EffronGrammarly CEO Rahul explains how the company is moving from grammar checks to end-to-end communication assistance—and why evals, user data, and measurable outcomes matter.
14:41ENTalking for 20 Minutes: How the Alexa Prize Turns Real Customers into a Testbed for Conversational AIゲスト Rohit Prasad · ホスト Lex FridmanRohit Prasad, head scientist of Amazon Alexa, explains the Alexa Prize grand challenge, how it is judged and why true conversation still needs reasoning.
1:16:17ENFaster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI Eraゲスト Nicole Forsgren · ホスト Lenny RachitskyThe creator of DORA and SPACE explains why most productivity metrics mislead, how AI changes flow and trust, and how to build a developer experience program that proves its value.
1:36:57ENDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding Assistantホスト Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.
1:24:01ENFrom Sandwich Math to Expert Data: Scale AI's CEO on What Actually Makes Models Smarterホスト Lenny RachitskyJason Droege explains what really happened with Meta's investment in Scale AI, how data labeling turned into expert work, and what Uber Eats taught him about building businesses.
57:21ENGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build Nextホスト Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
1:25:34ENShipping in Days: How Claude Code's Head of Product Runs a Team at AI Speedホスト Lenny RachitskyCat Wu, Head of Product for Claude Code and Cowork at Anthropic, explains how the PM role, hiring, tooling and culture change when features go from idea to users in a week or less.
58:57ENWhen the Model Learns to Look Around: Apollo Research on Testing o1 for Schemingホスト Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.
1:46:33ENFrom Chaos to a Failure Map: A Hands-On Primer on AI Evalsゲスト Hamel Husain, Shreya Shankar · ホスト Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.









