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슬라이드 5장9:58EN
Matthew Berman· 2024년 8월 2일Abstract 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 & performance에이전트 엔지니어링+2
1:07:05EN
Sequoia Capital· 2024년 7월 16일팟캐스트AlphaGo 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.에이전트에이전트 엔지니어링Reinforcement Learning+3
1:16:22EN
Cognitive Revolution "How AI Changes Everything"· 2024년 7월 9일팟캐스트He Spent 20 Hours Crafting a Prompt. DSPy Beat Him Anyway진행자 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 optimization에이전트 엔지니어링+3
59:11EN
Sequoia Capital· 2024년 6월 25일팟캐스트Don'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%.코딩 에이전트에이전트 엔지니어링평가(Evals)+3
1:37:07EN
Cognitive Revolution "How AI Changes Everything"· 2024년 6월 22일팟캐스트A Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.진행자 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.모델과 학습AI in healthcareMultimodal AI+3
49:50EN
Sequoia Capital· 2024년 6월 18일팟캐스트Unconstrained 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.에이전트에이전트 엔지니어링Agent orchestration+3
슬라이드1:00EN
Matthew Berman· 2024년 5월 13일Andrew 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 agents에이전트 엔지니어링Multi-agent systems
29:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 5월 2일팟캐스트 · 2명Devin Will Not Replace Engineers. It Will Multiply Them, Says Cognition’s Scott Wu진행자 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.코딩 에이전트에이전트 엔지니어링Developer productivity+3
슬라이드 4장16:22EN
Matthew Berman· 2024년 5월 2일Harrison 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
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 7장13:59EN
Matthew Berman· 2024년 4월 5일SWE-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.코딩 에이전트에이전트 엔지니어링개발 워크플로와 테스트+2
27:32EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 3월 28일팟캐스트 · 2명From a side project to 700 integrations: Harrison Chase on what still blocks agents진행자 Sarah Guo, Elad GilThe LangChain CEO walks through a two-year churn of patterns, and why memory, planning, and few-shot data still matter more than swapping models.에이전트에이전트 엔지니어링Agent memory+3
42:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 3월 7일팟캐스트 · 2명Meta’s $197 Billion Day Was a Partial Answer to AI’s $200 Billion Question진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil walk through Gemini, Mistral, NVIDIA’s upgrade cycle, Klarna’s support bot, and why the real AI spend still sits with the hyperscalers.기업과 전략AI Strategy엔터프라이즈 AI+3
슬라이드 4장55:29EN
Matthew Berman· 2024년 2월 24일Building a CrewAI Newsletter Team: Scraping, Summarizing and DebuggingMatthew Berman, Joe · Forward FutureMatthew Berman builds a two-agent newsletter prototype, works through input and scraping errors, and shows what still needs to be fixed.Multi-agent systems에이전트 엔지니어링Workflow automation+2
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
46:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 1월 18일팟캐스트 · 2명After a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the model진행자 Sarah Guo, Elad GilBeyang Liu on Cody, why keyword search still does most of RAG, and why CS fundamentals get more valuable as AI compresses the middleware.코딩 에이전트검색 증강 생성(RAG)컨텍스트 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
32:48EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 11월 16일팟캐스트 · 2명Fourteen People, $200 Million of Compute, and the Reliability Bottleneck for Agents진행자 Sarah Guo, Elad GilImbue co-founders Kanjun Qiu and Josh Albrecht on why agents fail, why language models cannot learn general algorithms, and why they are spending a giant round on GPUs rather than headcount.에이전트코딩 에이전트에이전트 엔지니어링+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
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