Canales actualizados recientemente

Elige uno para ver solo ese canalVer todos los canales →

Resultados

269 artículos
Ordenar
2 diapositivas6:53EN
Matthew Berman· 4 may 2023StableVicuna’s 2023 Release: An Early RLHF Chatbot Put to the TestMatthew Berman · Forward FutureMatthew Berman reviews the 13-billion-parameter model and tests poetry, simple code, reasoning and a resignation email.Open-weight modelsReinforcement LearningEvaluaciones+1
1:21:06EN
Cognitive Revolution "How AI Changes Everything"· 27 abr 2023PódcastEveryone Talks About RLHF. Almost Nobody Is Doing It.Presenta: Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.Producto y UXEvaluacionesObservabilidad y fiabilidad+3
5 diapositivas6:24EN
Matthew Berman· 6 abr 2023BloombergGPT: Mixing Financial and General Data for a Language ModelMatthew Berman · Forward FutureMatthew Berman examines the 2023 finance-focused research model, its training corpus, evaluation and decision not to release weights.IA en finanzasModelos y entrenamientoEvaluaciones+1
1:56:16EN
Cognitive Revolution "How AI Changes Everything"· 6 abr 2023PódcastThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.Presenta: Nathan LabenzOught's founders tell Nathan Labenz why open-ended reasoning has to be decomposed, supervised, and grounded—not scaled until it merely looks persuasive.RAG y conocimientoIngeniería de agentesEvaluaciones+3
1:23:53EN
Cognitive Revolution "How AI Changes Everything"· 17 mar 2023PódcastGPT-4, 24 Hours Later: No Safety Locks, a Captcha Hire, and a U.S.–China DeadlockPresenta: 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.SeguridadRed TeamingSeguridad y gobernanza+3
3 diapositivas11:53EN
Matthew Berman· 14 mar 2023Testing 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.OpenAIFoundation ModelsEvaluaciones+1
1:13:06EN
Lex Fridman· 19 ago 2019Pódcast · 2 vocesLockheed Martin's CTO on Autonomy, the Moon, and the Culture of Not Getting It WrongInvitado: Keoki Jackson · Presenta: 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.SeguridadSeguridad y gobernanzaValidación con humanos en el bucle+3
1:45:49EN
Cognitive Revolution "How AI Changes Everything"PódcastTrust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the CompanyPresenta: 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.AgentesWorld modelsReasoning & test-time compute+3
1:25:13EN
Lenny's PodcastPódcastCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a TeammatePresenta: 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.Agentes de programaciónCode review & verificationDeveloper productivity+3
1:33:50EN
Lenny's PodcastPódcastEvals Are the New PRDs: Inside Anthropic's Research Product TeamPresenta: 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.Producto y UXAI Product ManagementProduct Strategy+3
1:31:41EN
Lenny's PodcastPódcast · 2 vocesThe Worst Model You'll Ever Use: Kevin Weil on Building Products at OpenAI's PaceInvitado: Kevin Weil · Presenta: 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.Producto y UXProduct LeadershipAI Product Management+3
1:22:36EN
Lenny's PodcastPódcast · 2 vocesStop Chasing AI News: Chip Huyen on What Actually Makes AI Products BetterInvitado: Chip Huyen · Presenta: 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.Producto y UXAjuste finoGeneración aumentada por recuperación+3
1:07:08EN
Lenny's PodcastPódcast · 2 vocesIf the Model Is the Product, the Eval Is the PRD: Inside Mercor's RiseInvitado: Brendan Foody · Presenta: 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.Evaluaciones y observabilidadEvaluacionesData quality & curation+3
51:30EN
Unsupervised Learning: With Jacob EffronPódcastLess Email, Better Thinking: Grammarly’s CEO on AI That Augments CommunicationPresenta: 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.Producto y UXProduct StrategyIA empresarial+3
14:41EN
Lex FridmanPódcast · 2 vocesTalking for 20 Minutes: How the Alexa Prize Turns Real Customers into a Testbed for Conversational AIInvitado: Rohit Prasad · Presenta: 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.Producto y UXIA de vozAI research+3
1:16:17EN
Lenny's PodcastPódcast · 2 vocesFaster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI EraInvitado: Nicole Forsgren · Presenta: 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.Evaluaciones y observabilidadDeveloper productivityEvaluaciones+3
1:36:57EN
Unsupervised Learning: With Jacob EffronPódcastDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding AssistantPresenta: 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.Agentes de programaciónEvaluacionesGeneración aumentada por recuperación+3
1:24:01EN
Lenny's PodcastPódcastFrom Sandwich Math to Expert Data: Scale AI's CEO on What Actually Makes Models SmarterPresenta: 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.Modelos y entrenamientoCompany BuildingData quality & curation+3
57:21EN
Cognitive Revolution "How AI Changes Everything"PódcastGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build NextPresenta: Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.Modelos y entrenamientoBenchmarksAI cost & performance+3
1:25:34EN
Lenny's PodcastPódcastShipping in Days: How Claude Code's Head of Product Runs a Team at AI SpeedPresenta: 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.Agentes de programaciónProduct ManagementAI Product Management+3
58:57EN
Cognitive Revolution "How AI Changes Everything"PódcastWhen the Model Learns to Look Around: Apollo Research on Testing o1 for SchemingPresenta: 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.SeguridadAI securitySeguridad y gobernanza+3
1:46:33EN
Lenny's PodcastPódcast · 3 vocesFrom Chaos to a Failure Map: A Hands-On Primer on AI EvalsInvitado: Hamel Husain, Shreya Shankar · Presenta: Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.Evaluaciones y observabilidadEvaluacionesLiderazgo en ingeniería de IA+3