筛选结果
16 篇排序
1:29:02ENFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Explore主持 Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
1:18:49ENIf AGI Is Cheap Intelligent Labor, Cyber Defense Should Become Continuous Forensics主持 Nathan LabenzAsymmetric Security founder Alexis Carlier argues that assuming AGI means redesigning defense around proactive digital forensics instead of alert triage.
38:48ENTask Length Doubles Every Few Months. Nathan Labenz Still Wants Humans in Charge主持 Nathan LabenzAt Imagine AI Live, the Cognitive Revolution host maps structured AI agents against autonomous agentic systems—and tells businesses to keep final control.
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.
1:01:53ENHumans Wrote 1.3 Percent of the Tokens. The AI Lab Still Designed Working Nanobodies.主持 Nathan LabenzStanford's James Zou describes a GPT-4o research group that invented a protein-design pipeline for under $100 — and a sparse autoencoder that pulled an undocumented motif out of ESM-2.
1:29:00EN14,000 people applied. Thirty-three got in. The jobs are at Homeland Security.主持 Nathan LabenzMichael Boyce, director of the DHS AI Corps, tells Nathan Labenz how the largest civilian AI team in the U.S. government is being built — and what it is already shipping.
1:55:53EN → 简体中文AI 读论文已超过人类,却仍数不清原子主持 Nathan LabenzFuture House 科学负责人 Andrew White 梳理了语言模型在化学和生物学中已经能做什么,以及它们无法消除的瓶颈。
1:23:37ENNine of the top ten research ideas were Claude's主持 Nathan LabenzStanford PhD student Chenglei Si ran a blind study pitting Claude 3.5 Sonnet against more than a hundred NLP researchers on novel research ideas.
1:23:09EN → 简体中文AI 任务的合适大小,就是你能检查得了的那么大主持 Nathan LabenzElicit 联合创始人 Andreas Stuhlmüller 与 Jungwon Byun 讲述,一个十二人的研究助理如何把摘要中的幻觉数从 1.5 降到 0.5,大约每一周半发布一次更新,并把任务拆解视为在不依赖黑箱的前提下投入更多算力的办法。
1:28:37ENTwelve Hours After a GPT-4 Demo, He Turned a Decade-Old Legal Startup Around主持 Nathan LabenzPablo Arredondo, co-founder of CaseText and now VP of CoCounsel at Thomson Reuters, traces legal research from 19th-century citators to a retrieval-anchored GPT-4 product that law firms treat more like a colleague than a search box.
1:33:51EN → 简体中文GPT-4 写的 SQL 仍然跑不通。她给模型装上了一道护栏主持 Nathan LabenzShreya Rajpal 做了 Guardrails AI,让开发者能把“正确”的定义写下来,逐块校验,并把失败结果送回模型,而不是指望提示词靠得住。
1:28:43ENClinical Guidelines Are 11% Evidence. Curai’s Founder Still Wants GPT-4 in the Exam Room主持 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-4主持 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.
58:26ENSeventy Percent of the Inbox Is a Pitch: Matt Welsh on the First Wave of AI Agents主持 Nathan LabenzThe Fixie.ai founder maps copilot versus delegation, the missing appendages into our systems, and why agents will need guardrails, memory hygiene, and probably an earpiece.
1:56:16ENThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.主持 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.
1:25:46ENDon't Make the Tools Agentic: Flo Crivello on What Production Agents Actually Need主持 Nathan LabenzThe Lindy CEO tells Nathan Labenz that most working agents are intelligent workflows with human-designed control flow — and that scaffolding may still matter even if AGI arrives.









