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3,785 件
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スライド 7 枚36:45EN
Theo - t3․gg· 2026年5月4日Theo on the Microsoft–OpenAI Agreement and Amazon’s Cloud OpportunityTheo Browne · Ping LabsThe 2026 amendment changes exclusivity and revenue sharing while keeping Microsoft and OpenAI in a continuing partnership.OpenAIインフラとデプロイエンタープライズ AI+2
1:20:30EN
20VC with Harry Stebbings· 2026年5月4日ポッドキャスト · 2 人Tobi Lütke on Building Shopify, AI and the Future of Workゲスト Tobi Lütke · ホスト Harry StebbingsShopify’s CEO discusses long-term leadership, AI-assisted engineering and his views on employment and public policy.LeadershipFuture of WorkAI Adoption+2
スライド 2 枚1:23EN
Matthew Berman· 2026年5月3日Matthew Berman Demonstrates Codex Creating a Population SpreadsheetMatthew Berman · Forward FutureA short demonstration shows an AI agent using a web search and a spreadsheet skill to produce a chart.エージェントプロダクトと UXコーディングエージェント
1:14:23EN
20VC with Harry Stebbings· 2026年5月2日ポッドキャスト · 2 人Becca Lindquist on Clay’s Sales Hiring, Compensation and AIゲスト Becca Lindquist · ホスト Harry StebbingsClay’s head of sales explains how she evaluates candidates, designs incentives and builds customer champions in a product-led business.SalesHiringGo-to-Market+2
2:17:49ZH
Zhang Xiaojun Podcast· 2026年5月1日ポッドキャスト · 2 人苏煜:从逻辑智能体到语言智能体,走向专业化学习ゲスト 苏煜 · ホスト 张小珺研究者与张小珺梳理智能体技术史,讨论 OpenClaw、世界模型、界面与可靠性。AI agentsエージェント工学Human-AI Collaboration+2
42:57EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年5月1日ポッドキャスト · 2 人Inference Is the Last Market: Baseten’s 30x Yearホスト Sarah Guo, Elad GilCEO Tuhin Srivastava on a billion-dollar inference cloud, why the app layer survives, and a GPU crunch worse than the narrative.インフラとデプロイInferencePost-training+3
スライド 3 枚34:39EN
Theo - t3․gg· 2026年5月1日Claude Code’s Billing False Positive and Anthropic’s Developer Trust ProblemTheo Browne · T3Theo Browne examines a subscription billing false positive, explains prompt caching, and shares T3 Chat’s API costs.コーディングエージェントAnthropicAI cost & performance+2
スライド 10 枚1:42:41EN
Matthew Berman· 2026年5月1日Testing AI Reasoning, App Store Lookalikes and the Debate Over AnthropicMatthew Berman · Forward FutureIn a May 2026 livestream, Matthew Berman tests a car-wash prompt, discusses AI subscription limits and considers reported employee monitoring for model training.AI agentsBenchmarksPrompting & in-context learning+2
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月1日ポッドキャストThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.ホスト Nathan LabenzCoreWeave's Kyle Corbitt walks Nathan Labenz through GRPO, rubrics, RL environments, and why most reward hacks are easy to catch once you know to look.モデルと学習Reinforcement LearningPost-training+3
1:28:19EN
20VC with Harry Stebbings· 2026年4月30日ポッドキャスト · 3 人AI Compute, Private Equity and the Narrowing Exit: A 20VC Roundtableゲスト Jason Lemkin, Rory O’Driscoll · ホスト Harry StebbingsJason Lemkin and Rory O’Driscoll debate reported AI financing, software’s future and what private-equity losses could mean for venture investors.Venture CapitalAI cost & performanceエンタープライズ AI+2
スライド 4 枚35:10EN
Theo - t3․gg· 2026年4月30日GitHub Reliability, Merge Errors and Developer TrustTheo Browne · T3Theo Browne examines outages, a merge-queue incident, security and the future of open-source collaboration.開発ワークフローとテストオブザーバビリティと信頼性Open-source ecosystems+2
スライド 6 枚38:58EN
Theo - t3․gg· 2026年4月29日What Tech Stack Does Claude Code Choose? A Study and Its LimitsTheo Browne · T3Theo Browne examines coding-agent tool choices, DIY tendencies and examples comparing Claude Code with Codex.コーディングエージェント開発ワークフローとテストSoftware engineering+2
スライド17:26EN
Matthew Berman· 2026年4月29日Matthew Berman on Funding US Open-Weight AI in Competition With ChinaMatthew Berman · Forward FutureBerman argues that open models face a financing problem and proposes public support, hardware-backed development and specialized models.Open-weight modelsAI StrategyGeopolitics+2
スライド 2 枚17:56EN
Matthew Berman· 2026年4月28日Children, AI Sycophancy and Environmental Trade-offsMatthew Berman · Forward FutureMatthew Berman discusses a parent’s objections to a child using AI, then weighs supervised learning, chatbot reliability and data-center impacts.AI SafetyHuman-AI CollaborationMental Health+2
スライド54:06EN
Theo - t3․gg· 2026年4月28日Learning to Code and Finding Opportunities as a New DeveloperTheo Browne · T3Theo Browne reflects on the circumstances behind his first job and discusses feedback, community, AI-assisted learning and human connections.Career GrowthDeveloper productivitySoftware engineering+2
1:20:29EN
20VC with Harry Stebbings· 2026年4月27日ポッドキャスト · 2 人Adam Foroughi on AppLovin, AI and Building a Lean Companyゲスト Adam Foroughi · ホスト Harry StebbingsAppLovin’s CEO discusses staff cuts, AI-assisted engineering, compensation and public-market decisions, offering his account of a volatile company turnaround.Company BuildingLeadershipAI Adoption+2
1:35EN
Matthew Berman· 2026年4月27日DeepSeek V4 and the Cost of Frontier AI ModelsMatthew Berman · Forward FutureMatthew Berman argues that an open-weight Chinese model could put price pressure on US AI providers. The comparison depends on the workload, evaluation and cost assumptions.Foundation ModelsAI cost & performanceOpen-weight models+1
スライド 4 枚22:06EN
Theo - t3․gg· 2026年4月27日Markdown’s Simplicity and Complexity: Syntax, Extensions and SecurityTheo Browne · T3Theo Browne examines a critique of Markdown, from equivalent syntax to inline HTML and the complexity of document processing.Software engineeringProgramming Languages開発ワークフローとテスト+2
2:38:48EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月26日ポッドキャストA thousand searches for five cents, and a high score that did not require cheatingホスト Nathan LabenzOn a Cognitive Revolution morning show, Ceramic’s Anna Patterson collides cheap search with GPT-5.5’s clean Vending-Bench run, Zvi’s case for model welfare, and analog chips that cut matrix-multiply energy about thirtyfold.企業と戦略検索拡張生成(RAG)Search & retrieval+3
48:49EN
20VC with Harry Stebbings· 2026年4月25日ポッドキャスト · 2 人Amjad Masad on Replit, Coding Agents and the Future of Softwareゲスト Amjad Masad · ホスト Harry StebbingsReplit’s CEO discusses model routing, software economics, maintenance and the changing roles of builders and engineers.コーディングエージェントAI StrategyCompany Building+2
スライド 2 枚17:21EN
Matthew Berman· 2026年4月25日DeepSeek V4, Model Efficiency and the US–China AI DebateMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s April 2026 V4 preview and argues that efficient open-weight models raise questions for American AI providers and policymakers.Open-weight modelsAI cost & performanceGeopolitics+2
スライド 2 枚36:51EN
Theo - t3․gg· 2026年4月25日Fake GitHub Stars and Open-Source Traction: What the Numbers Can ShowTheo Browne · T3Theo Browne examines research on fake stars, challenges simple funding narratives and discusses broader project due diligence.Open-source ecosystemsData quality & curationVenture Capital+2
53:30EN
Matthew Berman· 2026年4月24日Thomas Kurian on Google Cloud’s TPUs, AI Agents and CybersecurityMatthew Berman, Thomas Kurian · Forward FutureThe Google Cloud CEO explains how Google allocates compute between its own models and competitors, designs infrastructure for agents, and approaches security and code review.インフラとデプロイSemiconductorsエンタープライズ AI+2
3:34:39EN
Zhang Xiaojun Podcast· 2026年4月24日ポッドキャスト · 2 人Luo Fuli on Agent Frameworks, Model Training, and Teamworkゲスト Luo Fuli · ホスト 张小珺Xiaomi’s model team leader discusses OpenClaw, long-context efficiency, post-training, and collaboration in a period of rapid change.AI agentsモデルと学習エージェント工学+2
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