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209 件
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48:18EN
Unsupervised Learning: With Jacob Effron· 2024年12月6日ポッドキャストNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroomホスト Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.モデルと学習Reasoning & test-time computeAGI(汎用人工知能)+3
1:55:53EN
Cognitive Revolution "How AI Changes Everything"· 2024年12月5日ポッドキャストAI Beats Humans at Reading Papers. It Still Cannot Count Atoms.ホスト Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.エージェントAI for science検索拡張生成(RAG)+3
1:27:33EN
Cognitive Revolution "How AI Changes Everything"· 2024年12月3日ポッドキャストA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a Dayホスト Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.エージェントエージェント工学Computer use+3
1:03:07EN
Sequoia Capital· 2024年11月26日ポッドキャストReasoning Hasn't Budged in Two Years. Dust Still Saved a Customer 8,000 HoursDust co-founders Gabriel Hubert and Stanislas Polu on multi-model agents, refusing to buy GPUs before product-market fit, and the jump from calculator tools to stochastic ones.エージェントエージェント工学エンタープライズ AI+3
スライド 5 枚10:57EN
Matthew Berman· 2024年11月16日Tracing a CrewAI Agent Workflow with LangtraceMatthew Berman · Forward FutureMatthew Berman builds a research-and-reporting crew, adds Langtrace, and inspects traces, token usage, timing and model costs.エージェント工学評価とオブザーバビリティAI cost & performance+1
スライド 7 枚1:42:56EN
Matthew Berman· 2024年11月12日Building a Research and Writing Flow with CrewAIMatthew Berman, João Moura · Forward FutureMatthew Berman and CrewAI founder João Moura build and debug a two-crew workflow for planning and drafting educational articles.Agent orchestrationエージェント工学Multi-agent systems+2
38:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年10月8日ポッドキャスト · 2 人Half of Production AI Is RAG. Fine-Tuning Almost Disappeared.ホスト Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.評価とオブザーバビリティ評価(Evals)検索拡張生成(RAG)+3
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2024年10月2日ポッドキャスト30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Thinkホスト Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.コーディングエージェントエージェント工学ファインチューニング+3
16:57EN
Matthew Berman· 2024年9月30日Jensen Huang and Marc Benioff on AI Agents and the Future of ComputingMatthew Berman, Jensen Huang, Marc Benioff · Forward FutureMatthew Berman comments on a 2024 Dreamforce discussion about agent collaboration, training, safety, and making AI tools practical.AI agentsエージェント工学モデルと学習+2
48:31EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年9月19日ポッドキャスト · 2 人A Call Center Contact Costs $13. A Company Agent Can Do It for Under a Dollarホスト Sarah Guo, Elad GilSierra cofounder and OpenAI chairman Bret Taylor tells No Priors why branded customer agents are shovel-ready, why RAG demos are not products, and how AI software should charge for the job done.エージェントエージェント工学Customer support automation+3
2:03:55EN
Cognitive Revolution "How AI Changes Everything"· 2024年9月18日ポッドキャストThe More You Constrain an Agent, the More You Can Trust Itホスト Nathan LabenzAgent.ai engineering lead Andrei Oprisan tells Nathan Labenz why narrow, highly prescribed workflows beat open-ended autonomy — and how a 12-person team shipped a free agent network past 40,000 users in a few months.エージェントエージェント工学Workflow automation+3
1:12:31EN
Sequoia Capital· 2024年8月27日ポッドキャストA Bare Model Closes 35% of Airline Changes. Sierra's Agents Clear 70% of Real Tickets.Clay Bavor on why putting a raw LLM in front of customers does not math, and how AgentOS, supervisor agents, and outcome pricing change the arithmetic.エージェントエージェント工学評価(Evals)+3
スライド 5 枚9:58EN
Matthew Berman· 2024年8月2日Abstract AI: A Proposed Routing Layer for Language ModelsMatthew Berman · Forward FutureMatthew Berman outlines a startup idea for choosing models and workflows by cost, speed and quality.Model routing & gatewaysAI cost & performanceエージェント工学+2
1:07:05EN
Sequoia Capital· 2024年7月16日ポッドキャストAlphaGo Combined Learning and Search. Language Models Only Did the First Half.Reflection AI's Misha Laskin tells Sequoia why prompted coding agents stall in the teens, and why the missing piece is still a ground-truth reward.エージェントエージェント工学Reinforcement Learning+3
1:16:22EN
Cognitive Revolution "How AI Changes Everything"· 2024年7月9日ポッドキャストHe Spent 20 Hours Crafting a Prompt. DSPy Beat Him Anywayホスト Nathan LabenzSander Schulhoff walks through The Prompt Report — a 78-page survey of what actually works when you prompt large language models.Prompting & in-context learningPrompt optimizationエージェント工学+3
59:11EN
Sequoia Capital· 2024年6月25日ポッドキャストDon't Train a Model. Factory's Founders Say Go Dig for GoldMatan Grinberg and Eno Reyes tell Sequoia's Training Data why they sell a fleet of job-specific droids on top of other people's models — and how that stack just took SWE-bench from 14% to 19%.コーディングエージェントエージェント工学評価(Evals)+3
1:37:07EN
Cognitive Revolution "How AI Changes Everything"· 2024年6月22日ポッドキャストA Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.ホスト Nathan LabenzGoogle researchers Vivek Natarajan and Khaled Saab walk Nathan Labenz through five medical-AI papers, from radiology reports to an AI doctor that still has to earn trust.モデルと学習AI in healthcareMultimodal AI+3
49:50EN
Sequoia Capital· 2024年6月18日ポッドキャストUnconstrained agents captivated Twitter. Custom ones are what ship.LangChain founder Harrison Chase tells Sequoia’s Training Data what an agent actually is, why AutoGPT stalled, and which cognitive architectures reach production.エージェントエージェント工学Agent orchestration+3
スライド1:00EN
Matthew Berman· 2024年5月13日Andrew Ng on Four Agentic AI Design PatternsMatthew Berman, Andrew Ng · Forward FutureA short excerpt identifies reflection, tools, planning and multi-agent collaboration as approaches to building AI agents.AI agentsエージェント工学Multi-agent systems
29:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年5月2日ポッドキャスト · 2 人Devin Will Not Replace Engineers. It Will Multiply Them, Says Cognition’s Scott Wuホスト Sarah Guo, Elad GilThe IOI champion behind Devin explains why an AI software engineer that you can watch over the shoulder creates more human engineers, not fewer.コーディングエージェントエージェント工学Developer productivity+3
スライド 4 枚16:22EN
Matthew Berman· 2024年5月2日Harrison Chase on Planning, Interface Design and Memory for AI AgentsMatthew Berman, Harrison Chase · Forward FutureThe LangChain CEO outlines open questions for agent builders, with commentary from Matthew Berman on oversight, workflows and memory.AI agentsAgent orchestrationAgent memory+2
スライド 9 枚19:09EN
Matthew Berman· 2024年4月28日OSWorld: Evaluating Computer-Use Agents in Real ApplicationsMatthew Berman · Forward FutureMatthew Berman explains the 2024 benchmark’s observation–action loop, task-specific checks and early results, with the limitations of its experimental setup.Computer use評価(Evals)Benchmarks+1
スライド 5 枚19:46EN
Matthew Berman· 2024年4月15日Building a CrewAI Financial-Analysis Team on Lightning AIMatthew Berman · Forward FutureMatthew Berman demonstrates a 2024 two-agent workflow, first using Groq and then connecting a cloud-hosted Ollama model.エージェント工学Multi-agent systems開発ワークフローとテスト+1
スライド 7 枚13:59EN
Matthew Berman· 2024年4月5日SWE-agent Tutorial: Navigating Repositories and Attempting GitHub FixesMatthew Berman, Carlos · Forward FutureMatthew Berman sets up a research coding agent, hits an installation problem and a cost limit, then shows an author’s successful SymPy benchmark example.コーディングエージェントエージェント工学開発ワークフローとテスト+2
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