최신 글
4,482개정렬
19:43EN
AI Engineer· 2026년 10월 26일Jack Wotherspoon on Building a Team of Managed AgentsJack Wotherspoon · Google DeepMindGoogle DeepMind’s Jack Wotherspoon introduces Gemini Managed Agents: cloud sandboxes that let teams run coding and research agents with a single API call. He explains how persistent environments, reusable skills, proxy-injected credentials, schedules, and specialized agents fit together.
53:04ENAI Engineer· 2026년 10월 26일Fuad Ali: Building a Feedback Loop to Improve AI AgentsFuad Ali · Arize AIAn Arize workshop connects traces, failure datasets, evaluations, proposed fixes and experiments while keeping human judgment in the loop.
20:55ENAI Engineer· 2026년 10월 26일Jesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
44:58EN
Citadel Securities· 2026년 10월 26일팟캐스트 · 2명Mario Draghi on Europe’s Growth, Energy and Security Choices게스트 Mario Draghi · 진행자 Lisa AbramowiczIn an October 2026 conversation with Lisa Abramowicz, the former ECB president discusses fiscal pressures, AI, energy and European integration.
1:33:33EN
Machine Learning Street Talk· 2026년 10월 26일팟캐스트 · 6명Kevin Hartnett on Lean, Mathematical Proof and the Limits of AI Verification게스트 Kevin Hartnett, Leonardo de Moura, Kevin Buzzard, Jeremy Avigad, Paul Lessard · 진행자 Tim ScarfeThe story of Lean shows how mathematicians can check increasingly complex arguments—and why a correct formal proof still leaves room for questions about meaning and understanding.
45:34ENCitadel Securities· 2026년 10월 26일팟캐스트 · 2명Henry Paulson on AI Risk, U.S.–China Relations and Crisis Leadership게스트 Henry M. Paulson, Jr. · 진행자 Jim EspositoThe former Treasury secretary discusses today’s economic risks and lessons from the 2008 financial crisis.
30:37EN
Theo - t3․gg· 2026년 10월 26일Theo’s Three Skills for Reviewing and Shipping with Coding AgentsTheo Browne · Ping LabsHow sol-loop, full-send and full-stop encode review, verification and different levels of merge authority.
18:27ENAI Engineer· 2026년 10월 26일Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.
23:48EN
20VC with Harry Stebbings· 2026년 10월 26일팟캐스트 · 2명Satya Nadella on Zero Trust for AI and Why Every Company Should Own Its Intelligence게스트 Satya Nadella · 진행자 Harry StebbingsThe Microsoft CEO argues that capable agents need security boundaries even as alignment research remains unsettled, and explains why firms should retain the value created by their own AI use.
30:11ZH
硅谷101· 2026년 10월 25일AI 如何重构跨境支付：从交易路由、风控到智能体商务게스트 Leo Li, Apple Gao · 진행자 陈茜硅谷101 从一笔跨境机票付款出发，拆解支付网络的复杂性，以及 Antom 如何把 AI 引入运营、风险判断和智能体交易。
17:56ENAI Engineer· 2026년 10월 25일How Bridgewater Keeps Its AI Analyst Inside Permission BoundariesNikhil Benesch, Aaron Linsky · turbopufferAaron Linsky and Nikhil Benesch explain why search over an enterprise vault must honor document permissions without sacrificing recall or speed. Their solution combines vector indexing with native filtering to search hundreds of millions of vectors in roughly 120 milliseconds.
35:19ENAI Engineer· 2026년 10월 25일SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.
0:26EN
Matthew Berman· 2026년 10월 25일Sam Altman on Human Values and Problem-Solving in an AI WorldSam Altman · OpenAIIn a short interview excerpt, Altman considers the enjoyment of solving hard problems and the human role in interpreting results.
20:58ENAI Engineer· 2026년 10월 25일Vinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.
18:31ENAI Engineer· 2026년 10월 25일Janie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.
0:36ENMatthew Berman· 2026년 10월 25일Kimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.
15:27ENAI Engineer· 2026년 10월 25일What AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.
19:37ENAI Engineer· 2026년 10월 25일Jay Sahnan and Arik Bird on Building Financial Agents for the Whole WebJay Sahnan, Arik Bird · BrowserbaseBrowserbase’s Jay Sahnan and Arik Bird show how browser agents reach financial data hidden behind logins and bot defenses. Their Ramp, Bill, and Stripe examples connect reliable cloud browsers with Stagehand’s more adaptive controls.
1:08EN
The Builders· 2026년 10월 25일Elon Musk Proposes Competitor Review Before AI Model Releases게스트 Elon Musk · 진행자 Walter IsaacsonA short exchange with Walter Isaacson about safety coordination.
1:25:47EN
Lenny's Podcast· 2026년 10월 25일팟캐스트 · 2명Rob Snyder’s PULL Framework for Finding Early Demand게스트 Rob Snyder · 진행자 Lenny RachitskyA practical conversation about customer urgency, alternatives, early sales and retention.
19:24ENAI Engineer· 2026년 10월 24일Building an Agent Regression Loop from Production TracesSofia Jakovcevic · Arize AISofia Jakovcevic demonstrates how to compare agent changes across safety, task completion and other dimensions before deployment.
1:50:48EN
Y Combinator· 2026년 10월 24일Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
27:09ENAI Engineer· 2026년 10월 24일Laurie Voss on the Product Engineer After AI Coding AgentsLaurie Voss · Arize AIAs code generation accelerates, Voss argues that review, operations and defining user needs become successive constraints—and that junior training must change.
0:21ENMatthew Berman· 2026년 10월 24일An AI-Generated Kimi Benchmark Chart Used Invented ScoresMatthew Berman · Forward FutureMatthew Berman asks for a graph of Kimi K3.1 Pro benchmarks, then discovers that the displayed figures are illustrative placeholders.더 보기4,482개 중 24개 표시