最新の記事
3,790 件並び順
18:27EN
AI Engineer· 2026年10月26日Daksh 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· 2026年10月26日ポッドキャスト · 2 人Satya Nadella on Zero Trust for AI and Why Every Company Should Own Its Intelligenceゲスト Satya Nadella · ホスト 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· 2026年10月25日AI 如何重构跨境支付：从交易路由、风控到智能体商务ゲスト Leo Li, Apple Gao · ホスト 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· 2026年10月25日How 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· 2026年10月25日SallyAnn 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· 2026年10月25日Sam 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· 2026年10月25日Vinoo 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· 2026年10月25日Janie 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· 2026年10月25日Kimi 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· 2026年10月25日What 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· 2026年10月25日Jay 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.
19:24ENAI Engineer· 2026年10月24日Building 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· 2026年10月24日Why 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· 2026年10月24日Laurie 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· 2026年10月24日An 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.
21:52EN
PragerU· 2026年10月24日Josef Witt-Doerring on Gen Z Mental Health, Isolation, and Psychiatric PrescribingShabbos Kestenbaum, Josef Witt-Doerring, Scott Galloway · PragerUOn The Brief, Shabbos Kestenbaum and psychiatrist Josef Witt-Doerring discuss why young adults are struggling, how prescribing incentives shape care, and the place of relationships and daily habits in treatment.
16:44ENAI Engineer· 2026年10月24日How Bridgewater Built the Vault for Human Researchers and AI AgentsSam Green, Aaron Linsky · Bridgewater AssociatesSam Green and Aaron Linsky explain how Bridgewater organized more than 100 million documents and built search and proactive research tools around them.
25:50ENMatthew Berman· 2026年10月24日Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.
1:13:26EN20VC with Harry Stebbings· 2026年10月24日ポッドキャスト · 2 人Naveen Rao on Energy, AI Hardware, Verification and the Future of Roboticsゲスト Naveen Rao · ホスト Harry StebbingsThe Unconventional AI founder argues that energy efficiency will shape AI hardware, while the growing volume of model output makes verification more valuable.
0:43EN
Theo - t3․gg· 2026年10月23日Theo Distinguishes Security Vulnerabilities from Active AttacksTheo Browne · Ping LabsA short explanation of why disclosed software flaws and reported attacks are different kinds of security news.
32:20ENMatthew Berman· 2026年10月23日Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.
0:54ENMatthew Berman· 2026年10月23日Sam Altman: Seek Major Life Advice From People, Not AISam Altman · OpenAIThe OpenAI CEO distinguishes practical AI assistance from consequential life advice and argues for assistants that can push back.
34:11EN
GOTO Conferences· 2026年10月23日Anatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.
1:03:37ENMatthew Berman· 2026年10月23日Matthew Berman’s Team Tests Kimi K3.1 on Animation, Games, and ChartsMatthew Berman, Alex, Brian · Forward FutureA live team AMA turns into an informal test of Kimi K3.1, from personal-agent workflows to motion graphics, a browser game, and a benchmark chart.もっと見る3,790 件中 24 件を表示