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186 件
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33:18EN
Matthew Berman· 2025年5月1日Zuckerberg and Nadella on AI Coding, Agents and the Next Software StackMatthew Berman, Mark Zuckerberg, Satya Nadella · Forward FutureMatthew Berman examines their 2025 LlamaCon conversation about AI-assisted development, open models and changing workflows.コーディングエージェントエージェント工学AI Strategy+2
スライド 7 枚14:04EN
Matthew Berman· 2025年4月29日Qwen3: Open Weights, Adjustable Reasoning and Tool UseMatthew Berman · Forward FutureMatthew Berman reviews the April 2025 Qwen3 family, its benchmark claims, training pipeline and local demonstration.Open-weight modelsモデルと学習Reasoning & test-time compute+2
スライド 4 枚19:06EN
Matthew Berman· 2025年4月25日Sleep-Time Compute: Preparing AI Context Before a QuestionMatthew Berman · Forward FutureMatthew Berman reviews a 2025 paper on moving some reasoning ahead of a user query, and explains where its experiments found benefits and limits.Reasoning & test-time computeAgent memoryAI cost & performance+2
30:46EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年4月24日ポッドキャスト · 2 人Deep Research Turned Web Browsing into a Trainable Problemホスト Sarah Guo, Elad GilOpenAI researcher Isa Fulford explains why a side project on read-only synthesis became an agent, when reinforcement fine-tuning is worth it, and why models will hack the search engine you gave them.エージェントエージェント工学Reinforcement Learning+3
スライド 7 枚15:46EN
Matthew Berman· 2025年4月16日OpenAI o3 and o4-mini: Tool Use, Benchmarks and the First Codex CLIMatthew Berman · Forward FutureMatthew Berman reviews OpenAI’s April 2025 reasoning-model release, a scientific image-analysis demonstration and the debut of its terminal coding agent.OpenAIReasoning & test-time computeBenchmarks+2
41:52EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年4月10日ポッドキャスト · 2 人Mercor Hit $100 Million ARR Teaching Models to Hire. Humans Now Write the Exams.ホスト Sarah Guo, Elad GilBrendan Foody tells Sarah Guo and Elad Gil how Mercor automated recruiting for frontier labs — and why building evals may become the world's most common knowledge job.企業と戦略評価(Evals)エージェント工学+3
1:26:21EN
Cognitive Revolution "How AI Changes Everything"· 2025年4月10日ポッドキャストFor under $10, Google's AI independently recovered a lab result nobody had publishedホスト Nathan LabenzVivek Natarajan and Anil Palepu tell Nathan Labenz how AMIE beats primary-care doctors on treatment plans, and how Co-Scientist matched Imperial College's unpublished bacterial-resistance mechanism.エージェントAI in healthcareAI for science+3
1:26:19EN
Sequoia Capital· 2025年4月8日ポッドキャストHe turned down a billion dollars for a world with a billion developersReplit CEO Amjad Masad tells Sequoia’s Training Data why a six-person company walked away from a life-changing offer, and why a billion people writing software is a better end state than AGI as universal basic income.コーディングエージェントエージェント工学Developer productivity+3
2:14:59EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月29日ポッドキャストAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way Downホスト Nathan LabenzThe Firebase co-founder argues that workflow software is already obsolete, that MCP is optional, and that the only durable advantage left for an AI startup is speed.エージェントエージェント工学コンテキストエンジニアリング+3
1:01:53EN
Unsupervised Learning: With Jacob Effron· 2025年3月28日ポッドキャストOpen-source models are 5% of enterprise use — and GPT wrappers wonホスト Jacob EffronLatent Space's Swyx and Alessio join Redpoint to map what actually has product-market fit in AI, and why the application layer is the fight that matters.企業と戦略Product-Market FitAI Strategy+3
1:25:12EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月27日ポッドキャストHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line Repoホスト Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.コーディングエージェントコンテキストエンジニアリング検索拡張生成(RAG)+3
43:04EN
Sequoia Capital· 2025年3月25日ポッドキャスト750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.エージェントエージェント工学Prompting & in-context learning+3
50:35EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年3月13日ポッドキャスト · 2 人Copilot Already Writes Half the Code. GitHub's CEO Says Agents Still Have Four Gates to Clearホスト Sarah Guo, Elad GilThomas Dohmke on agent mode, why median developers are not going anywhere, and how AI is repricing the tools that write software.コーディングエージェント開発ワークフローとテストエージェント工学+3
9:02EN
Matthew Berman· 2025年3月13日Dario Amodei’s 2025 AI Coding Forecast and Matthew Berman’s ResponseMatthew Berman, Dario Amodei, Mark Zuckerberg · Forward FutureBerman considers a rapid forecast for AI-written code, the rise of coding agents, and speculative longer-term changes to software work.コーディングエージェントFuture of WorkVibe Coding+2
スライド 3 枚27:32EN
Matthew Berman· 2025年3月12日OpenAI’s Responses API and Agents SDK: A Launch WalkthroughMatthew Berman · Forward FutureMatthew Berman reacts to a launch demonstration of web and file search, computer use, agent handoffs and tracing.エージェント工学エージェントMCP とツール+1
54:10EN
Sequoia Capital· 2025年3月11日ポッドキャストHarvey Built Legal AI for the Work the Next Model Still Cannot DoCEO Winston Weinberg on citations, process data, and the unscalable tactics that won over century-old law firms.企業と戦略エンタープライズ AIProduct Strategy+3
32:46EN
Sequoia Capital· 2025年2月25日ポッドキャストDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.エージェントエージェント工学Reinforcement Learning+3
44:34EN
Unsupervised Learning: With Jacob Effron· 2025年2月19日ポッドキャストThe Cheaper Intelligence Gets, the More of It We'll Buyホスト Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.エージェントエージェント工学Reinforcement Learning+3
1:30:28EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月12日ポッドキャストA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative Societyホスト Nathan LabenzThe same donor game, run for ten generations, can bank 32,000 resource units if everyone cooperates—and three frontier models miss that ceiling by an order of magnitude.エージェントMulti-agent systems安全性とガバナンス+3
57:11EN
Unsupervised Learning: With Jacob Effron· 2025年1月30日ポッドキャストA Million Tokens Cannot Write a Good Jokeホスト Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.評価とオブザーバビリティ評価(Evals)Benchmarks+3
52:30EN
Sequoia Capital· 2025年1月28日ポッドキャストMove 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.エージェントReinforcement Learningエージェント工学+3
1:01:30EN
Matthew Berman· 2024年12月31日AutoGen and AG2: Chi Wang and Qingyun Wu on Building Multi-Agent SystemsMatthew Berman, Chi Wang, Qingyun Wu · Forward FutureThe AutoGen creators trace their open-source journey and explain how they approach agent workflows, human oversight and the move to AG2.Multi-agent systemsエージェント工学Agent orchestration+2
スライド 5 枚19:06EN
Matthew Berman· 2024年12月28日Building Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.エージェント工学エージェント評価(Evals)+1
27:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年12月26日ポッドキャスト · 2 人After adding $100 billion a month, Jensen Huang says NVIDIA is selling the data centerホスト Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.企業と戦略AI Strategyインフラとデプロイ+3
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