Ergebnisse
269 ArtikelSortieren
10:23ENTesting Hosted Falcon 40B and Document Chat in h2oGPTMatthew Berman · Forward FutureMatthew Berman tries H2O.ai’s 2023 hosted Falcon 40B interface on coding, writing and reasoning prompts, then demonstrates document chat.
11:49ENTesting Wizard-Vicuna 30B: Responses, Reasoning, and CodeMatthew Berman · Forward FutureMatthew Berman examines a model marketed as uncensored, demonstrates a 2023 cloud setup, and runs an informal collection of tests.
1:33:51ENGPT-4 still writes SQL that will not run. She put a guardrail on the modelModeration: Nathan LabenzShreya Rajpal built Guardrails AI so developers can encode what “correct” means, validate the pieces, and send failures back to the model instead of hoping the prompt holds.
1:25:35ENTwo and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical SchoolModeration: Nathan LabenzVivek Natarajan walks Nathan Labenz through Med-PaLM and Med-PaLM 2: the data-light techniques, the nine-axis clinician evals, and why a high USMLE-style score is the wrong trophy.
42:18ENTen Percent of Search Is Health — and the Doctor Is Googling TooModeration: Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.
1:28:43ENClinical Guidelines Are 11% Evidence. Curai’s Founder Still Wants GPT-4 in the Exam RoomModeration: Nathan LabenzNeal Khosla of Curai Health argues that large language models already match median U.S. physicians on today’s tests — and that the real work is scaffolding, supervision, and a doctor’s signature.
58:24ENAmong 100 Random Doctors, Zak Kohane Would Be Surprised If One Beat GPT-4Moderation: Nathan LabenzHarvard's biomedical informatics chair on a rare newborn case, why drug-style trials will not certify a general medical model, and why the AI should still work for the patient.
6:53ENStableVicuna’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.
1:21:06ENEveryone Talks About RLHF. Almost Nobody Is Doing It.Moderation: Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.
6:24ENBloombergGPT: 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.
1:56:16ENThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.Moderation: 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.
1:23:53ENGPT-4, 24 Hours Later: No Safety Locks, a Captcha Hire, and a U.S.–China DeadlockModeration: 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 WrongGast: Keoki Jackson · Moderation: 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 CompanyModeration: 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 TeammateModeration: 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 TeamModeration: 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 PaceGast: Kevin Weil · Moderation: 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 BetterGast: Chip Huyen · Moderation: 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 RiseGast: Brendan Foody · Moderation: 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 CommunicationModeration: 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 AIGast: Rohit Prasad · Moderation: 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 EraGast: Nicole Forsgren · Moderation: 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 AssistantModeration: 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.
Mehr laden24 von 269 angezeigt









