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122 件
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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
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
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 4 枚14:58EN
Matthew Berman· 2024年3月30日OpenDevin’s Early Coding Agent: A 2024 Installation and DemoMatthew Berman · Forward FutureMatthew Berman installs an early open-source coding-agent project and tries a calculator and a simple web page, while encountering setup and browser issues.コーディングエージェントエージェント工学Software engineering+1
4:56EN
Cognitive Revolution "How AI Changes Everything"· 2024年2月1日ポッドキャストIf the Mind Is a Tool, AI Looks Less Like a Threatホスト Nathan LabenzYohei Nakajima and Nathan Labenz pause a TED AI talk to connect agent-building habits with East–West ideas of identity.エージェントエージェント工学Knowledge graphs+3
1:45:21EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月30日ポッドキャスト600,000 Attack Prompts, and Nearly 40% Still Pwned GPT-4ホスト Nathan LabenzSander Schulhoff walks Nathan Labenz through the prompting habits that still work, the role-play myth that does not, and the global HackAPrompt contest that mapped how language models get hijacked.セキュリティと安全性Prompt injectionAI security+3
スライド 4 枚15:11EN
Matthew Berman· 2024年1月25日Building a Transcript-to-Article Team in AutoGen StudioMatthew Berman · Forward FutureMatthew Berman configures a retrieval skill, two agents and a group workflow, then troubleshoots missing credentials and output.エージェントエージェント工学
1:43:07EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月20日ポッドキャストAn Agent Posted Five Tweets — and 5,000 People Didn't Noticeホスト Nathan LabenzMultiOn founder Div Garg walks Cognitive Revolution through what web agents can actually do in early 2024, what they cost, and why guardrails have to sit outside the model.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
1:50:57EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月12日ポッドキャストTwenty-Eight Days After GPT-4, an AI Designed and Ran a Chemistry Experimentホスト Nathan LabenzGabe Gomes and his Carnegie Mellon students built Coscientist, a language-model agent that plans, codes, and executes real experiments on a remote cloud lab.エージェントAI for scienceエージェント工学+3
1:06:39EN
Unsupervised Learning: With Jacob Effron· 2024年1月9日ポッドキャストOpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Yearsホスト Jacob EffronLogan Kilpatrick on picking GPT-3.5 versus GPT-4, why plugins stalled, and why the public internet is not ready for autonomous agents.企業と戦略AI StrategyPrompting & in-context learning+3
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月2日ポッドキャストIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%ホスト Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.エージェントエージェント工学Reasoning & test-time compute+3
1:14:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月8日ポッドキャストDevDay Probably Created Thousands of Startups, Says OpenAI's Logan Kilpatrickホスト Nathan LabenzThe day after OpenAI's first developer conference, Dev Relations lead Logan Kilpatrick tells Nathan Labenz why thin wrappers were never companies, why agents were deliberately not shipped fully autonomous, and what $2 million custom models are for.企業と戦略Product Strategyエージェント工学+3
スライド 6 枚10:13EN
Matthew Berman· 2023年10月28日Building a Business Chatbot with GPTBots.aiMatthew Berman · Forward FutureIn a sponsored 2023 walkthrough, Matthew Berman configures an assistant, adds business knowledge, corrects a response and builds a branching flow.AI agentsプロダクトと UXエージェント工学+1
スライド 6 枚38:07EN
Matthew Berman· 2023年10月26日AutoGen Advanced Tutorial: Configuration, Memory, Retrieval and ToolsMatthew Berman · Forward FutureMatthew Berman walks through the 2023 AutoGen interface for multi-agent configuration, caching, retrieval, teachable memory and function calls.エージェント工学Agent orchestration検索拡張生成(RAG)+2
1:25:11EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月26日ポッドキャスト105 lines of code, a million impressions, and a VC who refused to found the companyホスト Nathan LabenzBabyAGI creator Yohei Nakajima tells Nathan Labenz how a weekend prototype set off the agent wave — and why he went back to writing checks.エージェントエージェント工学Agent orchestration+3
スライド 4 枚7:02EN
Matthew Berman· 2023年10月18日Connecting AutoGen to a RunPod-Hosted Model with Text Generation WebUIMatthew Berman · Forward FutureIn a 2023 walkthrough, Matthew Berman connects AutoGen to Dolphin 2.1 Mistral 7B through an OpenAI-compatible API and tests a small coding task.エージェント工学Open-weight modelsMulti-agent systems+2
スライド 5 枚15:03EN
Matthew Berman· 2023年10月10日A 2023 AutoGen Tutorial: Local Agent Setup and Code ExecutionMatthew Berman · Forward FutureMatthew Berman builds a local assistant and user-proxy workflow, then tests how the agents generate and run Python. AutoGen’s packages and APIs have changed since this tutorial.Multi-agent systemsエージェント工学コーディングエージェント+2
1:32:41EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月5日ポッドキャストThere are maybe 5,000 people who can train frontier models. The rest need AI engineersホスト Nathan LabenzSwyx of Latent Space tells Nathan Labenz how a new job is forming, why OpenAI will Sherlock its developers, and what still does not count as an agent.企業と戦略エージェント工学コーディングエージェント+3
55:13EN
Cognitive Revolution "How AI Changes Everything"· 2023年9月7日ポッドキャストTwo Days to a Prototype: How a16z Turned a Stanford Paper Into AI Townホスト Nathan LabenzA companion named Alice, a weekend Phaser hack, and Martin Casado's argument that models will never replace formal languages.エージェントエージェント工学Agent memory+3
1:39:53EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月8日ポッドキャストUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligenceホスト Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.コーディングエージェントDeveloper productivityAI startups & small teams+3
59:41EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月13日ポッドキャストHumans Are Single-Threaded. MULTI·ON Wants 100 Agents Running Anywayホスト Nathan LabenzStanford PhD dropout Div Garg put a personal agent in Chrome so it can reuse your logins, ask for help when it stalls, and stop before it hits Buy.エージェントPersonal agentsComputer use+3
スライド 5 枚6:03EN
Matthew Berman· 2023年5月3日BabyAGI UI: A 2023 Walkthrough of the Task-Planning InterfaceMatthew Berman · Forward FutureMatthew Berman installs an early web interface for BabyAGI and demonstrates its task-generation loop with a sample objective.AI agentsエージェント工学Open-source ecosystems
58:26EN
Cognitive Revolution "How AI Changes Everything"· 2023年4月25日ポッドキャストSeventy Percent of the Inbox Is a Pitch: Matt Welsh on the First Wave of AI Agentsホスト Nathan LabenzThe Fixie.ai founder maps copilot versus delegation, the missing appendages into our systems, and why agents will need guardrails, memory hygiene, and probably an earpiece.エージェントエージェント工学Agent memory+3
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