絞り込み結果
192 件並び順
1:06:39EN
Unsupervised Learning: With Jacob Effron· 2024年1月9日ポッドキャストOpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Yearsホスト 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.
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月2日ポッドキャストIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%ホスト Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.
32:48EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年11月16日ポッドキャスト · 2 人Fourteen People, $200 Million of Compute, and the Reliability Bottleneck for Agentsホスト Sarah Guo, Elad GilImbue co-founders Kanjun Qiu and Josh Albrecht on why agents fail, why language models cannot learn general algorithms, and why they are spending a giant round on GPUs rather than headcount.
1:23:10ENCognitive Revolution "How AI Changes Everything"· 2023年9月19日ポッドキャストLuxury Purses Under $500 Beat a Bank's Fraud Modelホスト Nathan LabenzArthur.ai CEO Adam Wenchel on boundary attacks, LLM firewalls, and why a model that eats raw text cannot be secured from the inside.
55:08ENCognitive Revolution "How AI Changes Everything"· 2023年8月29日ポッドキャストOne Model Inside 38 Products: Paige Bailey on How Google Trains and Ships PaLM 2ホスト Nathan LabenzAt Google I/O in May 2023, PaLM 2 arrived already running in more than two dozen products — and its lead product manager walks through what that actually took.
39:45ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年7月27日ポッドキャスト · 2 人Palantir's 13th Employee: The Model Is a Stochastic Genie. Ontology Is the Stake That Tethers Itホスト Sarah Guo, Elad GilCTO Shyam Sankar on 550 microservices, air-gapped submarines, and why Palantir's ontology is what large language models were waiting for.
12:20EN
Matthew Berman· 2023年7月10日Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.
54:00EN
20VC with Harry Stebbings· 2023年6月30日ポッドキャスト · 2 人Douwe Kiela on Data, Retrieval and Enterprise AIゲスト Douwe Kiela · ホスト Harry StebbingsThe Contextual AI CEO discusses language model trade-offs, evaluation, open models and the hurdles to enterprise use.
18:08ENMatthew Berman· 2023年6月29日Six Language Models Compared on an Informal 2023 Prompt SetMatthew Berman · Forward FutureMatthew Berman tests coding, writing and reasoning with H2O GPT, finding a tie under a small and subjective rubric.
11:49ENMatthew Berman· 2023年6月1日Testing 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.
1:33:51ENCognitive Revolution "How AI Changes Everything"· 2023年5月23日ポッドキャストGPT-4 still writes SQL that will not run. She put a guardrail on the modelホスト 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.
1:25:35ENCognitive Revolution "How AI Changes Everything"· 2023年5月21日ポッドキャストTwo and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical Schoolホスト 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.
42:18ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年5月18日ポッドキャスト · 2 人Ten Percent of Search Is Health — and the Doctor Is Googling Tooホスト 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.
1:28:43ENCognitive Revolution "How AI Changes Everything"· 2023年5月16日ポッドキャストClinical Guidelines Are 11% Evidence. Curai’s Founder Still Wants GPT-4 in the Exam Roomホスト 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.
58:24ENCognitive Revolution "How AI Changes Everything"· 2023年5月11日ポッドキャストAmong 100 Random Doctors, Zak Kohane Would Be Surprised If One Beat GPT-4ホスト 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.
1:21:06ENCognitive Revolution "How AI Changes Everything"· 2023年4月27日ポッドキャストEveryone Talks About RLHF. Almost Nobody Is Doing It.ホスト Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.
1:56:16ENCognitive Revolution "How AI Changes Everything"· 2023年4月6日ポッドキャストThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.ホスト 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.
1:23:53ENCognitive Revolution "How AI Changes Everything"· 2023年3月17日ポッドキャストGPT-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.
1:13:06EN
Lex Fridman· 2019年8月19日ポッドキャスト · 2 人Lockheed 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.
1:45:49ENCognitive Revolution "How AI Changes Everything"ポッドキャストTrust 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.
1:25:13EN
Lenny's PodcastポッドキャストCodex 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.
1:33:50ENLenny's PodcastポッドキャストEvals 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.
1:31:41ENLenny's Podcastポッドキャスト · 2 人The 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.
1:22:36ENLenny's Podcastポッドキャスト · 2 人Stop 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.もっと見る192 件中 24 件を表示