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슬라이드 9장19:09EN
Matthew Berman· 2024년 4월 28일OSWorld: 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 use평가(Evals)Benchmarks+1
슬라이드 4장14:58EN
Matthew Berman· 2024년 3월 30일OpenDevin’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.코딩 에이전트에이전트 엔지니어링Software engineering+1
4:56EN
Cognitive Revolution "How AI Changes Everything"· 2024년 2월 1일팟캐스트If the Mind Is a Tool, AI Looks Less Like a Threat진행자 Nathan LabenzYohei Nakajima and Nathan Labenz pause a TED AI talk to connect agent-building habits with East–West ideas of identity.에이전트에이전트 엔지니어링Knowledge graphs+3
1:45:21EN
Cognitive Revolution "How AI Changes Everything"· 2024년 1월 30일팟캐스트600,000 Attack Prompts, and Nearly 40% Still Pwned GPT-4진행자 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.보안과 안전Prompt injectionAI security+3
슬라이드 4장15:11EN
Matthew Berman· 2024년 1월 25일Building 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.에이전트에이전트 엔지니어링
1:43:07EN
Cognitive Revolution "How AI Changes Everything"· 2024년 1월 20일팟캐스트An Agent Posted Five Tweets — and 5,000 People Didn't Notice진행자 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.에이전트에이전트 엔지니어링컨텍스트 엔지니어링+3
1:50:57EN
Cognitive Revolution "How AI Changes Everything"· 2024년 1월 12일팟캐스트Twenty-Eight Days After GPT-4, an AI Designed and Ran a Chemistry Experiment진행자 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.에이전트AI for science에이전트 엔지니어링+3
1:06:39EN
Unsupervised Learning: With Jacob Effron· 2024년 1월 9일팟캐스트OpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Years진행자 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.기업과 전략AI StrategyPrompting & in-context learning+3
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023년 12월 2일팟캐스트If Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%진행자 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.에이전트에이전트 엔지니어링Reasoning & test-time compute+3
1:14:48EN
Cognitive Revolution "How AI Changes Everything"· 2023년 11월 8일팟캐스트DevDay Probably Created Thousands of Startups, Says OpenAI's Logan Kilpatrick진행자 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.기업과 전략Product Strategy에이전트 엔지니어링+3
슬라이드 6장10:13EN
Matthew Berman· 2023년 10월 28일Building 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 agents제품과 UX에이전트 엔지니어링+1
슬라이드 6장38:07EN
Matthew Berman· 2023년 10월 26일AutoGen 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.에이전트 엔지니어링Agent orchestration검색 증강 생성(RAG)+2
1:25:11EN
Cognitive Revolution "How AI Changes Everything"· 2023년 10월 26일팟캐스트105 lines of code, a million impressions, and a VC who refused to found the company진행자 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.에이전트에이전트 엔지니어링Agent orchestration+3
슬라이드 4장7:02EN
Matthew Berman· 2023년 10월 18일Connecting 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.에이전트 엔지니어링Open-weight modelsMulti-agent systems+2
슬라이드 5장15:03EN
Matthew Berman· 2023년 10월 10일A 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 systems에이전트 엔지니어링코딩 에이전트+2
1:32:41EN
Cognitive Revolution "How AI Changes Everything"· 2023년 10월 5일팟캐스트There are maybe 5,000 people who can train frontier models. The rest need AI engineers진행자 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.기업과 전략에이전트 엔지니어링코딩 에이전트+3
55:13EN
Cognitive Revolution "How AI Changes Everything"· 2023년 9월 7일팟캐스트Two Days to a Prototype: How a16z Turned a Stanford Paper Into AI Town진행자 Nathan LabenzA companion named Alice, a weekend Phaser hack, and Martin Casado's argument that models will never replace formal languages.에이전트에이전트 엔지니어링Agent memory+3
1:39:53EN
Cognitive Revolution "How AI Changes Everything"· 2023년 8월 8일팟캐스트Under 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence진행자 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.코딩 에이전트Developer productivityAI startups & small teams+3
59:41EN
Cognitive Revolution "How AI Changes Everything"· 2023년 7월 13일팟캐스트Humans Are Single-Threaded. MULTI·ON Wants 100 Agents Running Anyway진행자 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.에이전트Personal agentsComputer use+3
슬라이드 5장6:03EN
Matthew Berman· 2023년 5월 3일BabyAGI 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 agents에이전트 엔지니어링Open-source ecosystems
58:26EN
Cognitive Revolution "How AI Changes Everything"· 2023년 4월 25일팟캐스트Seventy Percent of the Inbox Is a Pitch: Matt Welsh on the First Wave of AI Agents진행자 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.에이전트에이전트 엔지니어링Agent memory+3
1:56:16EN
Cognitive Revolution "How AI Changes Everything"· 2023년 4월 6일팟캐스트They Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.진행자 Nathan LabenzOught's founders tell Nathan Labenz why open-ended reasoning has to be decomposed, supervised, and grounded—not scaled until it merely looks persuasive.RAG와 지식에이전트 엔지니어링평가(Evals)+3
1:25:46EN
Cognitive Revolution "How AI Changes Everything"· 2023년 3월 22일팟캐스트Don't Make the Tools Agentic: Flo Crivello on What Production Agents Actually Need진행자 Nathan LabenzThe Lindy CEO tells Nathan Labenz that most working agents are intelligent workflows with human-designed control flow — and that scaffolding may still matter even if AGI arrives.에이전트에이전트 엔지니어링Personal agents+3
1:45:49EN
Cognitive Revolution "How AI Changes Everything"팟캐스트Trust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the Company진행자 Nathan LabenzAndreas Stuhlmüller and Jungwon Byun explain how Elicit keeps frontier models checkable for high-stakes science, and where they think AI reasoning is heading.에이전트World modelsReasoning & test-time compute+3
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