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58 件
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トピック検索拡張生成（RAG）
1:23:09EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月3日ポッドキャストThe Right Size of an AI Task Is Whatever You Can Checkホスト Nathan LabenzElicit founders Andreas Stuhlmüller and Jungwon Byun walk through how a twelve-person research assistant cut summary hallucinations from 1.5 to 0.5, ships about every week and a half, and treats task decomposition as the way to spend more compute without a black box.RAG とナレッジ検索拡張生成（RAG）Search & retrieval+3
27:32EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年3月28日ポッドキャスト · 2 人From a side project to 700 integrations: Harrison Chase on what still blocks agentsホスト 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.エージェントエージェント工学Agent memory+3
1:28:37EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月14日ポッドキャストTwelve Hours After a GPT-4 Demo, He Turned a Decade-Old Legal Startup Aroundホスト Nathan LabenzPablo Arredondo, co-founder of CaseText and now VP of CoCounsel at Thomson Reuters, traces legal research from 19th-century citators to a retrieval-anchored GPT-4 product that law firms treat more like a colleague than a search box.企業と戦略検索拡張生成（RAG）評価（Evals）+3
42:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年3月7日ポッドキャスト · 2 人Meta’s $197 Billion Day Was a Partial Answer to AI’s $200 Billion Questionホスト 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.企業と戦略AI Strategyエンタープライズ AI+3
1:06:54EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月5日ポッドキャストGoogle Gives You 33 Million Results. Exa Wants 54.ホスト Nathan LabenzWill Bryk, CEO of Exa, tells Nathan Labenz why search and research are different jobs, and why an AI librarian for the web has to be neural from the first filter.RAG とナレッジSearch & retrieval検索拡張生成（RAG）+3
1:32:19EN
Cognitive Revolution "How AI Changes Everything"· 2024年2月29日ポッドキャストHis 2018 Prompting Paper Was Rejected. His Search API Now Beats Googleホスト Nathan LabenzRichard Socher traces You.com from a rejected unified NLP model to an LLM-native web index, three assistant modes, and a very low P(doom).プロダクトと UX検索拡張生成（RAG）Search & retrieval+3
31:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月22日ポッドキャスト · 2 人Bolt Memory onto GPT-4 and Cut Hallucinations by up to 50%ホスト Sarah Guo, Elad GilPinecone CEO Edo Liberty tells Sarah Guo and Elad Gil how RAG, serverless vectors, and keeping knowledge outside the model make LLMs more reliable.RAG とナレッジ検索拡張生成（RAG）Vector search+3
42:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月15日ポッドキャスト · 2 人Notion’s Ivan Zhao: RAG Will Make Organizing Optionalホスト Sarah Guo, Elad GilThe Notion CEO tells No Priors why he bet the company on GPT-4, why embeddings matter as much as agents, and why software is entering a bundling cycle.RAG とナレッジ検索拡張生成（RAG）Embeddings+3
46:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年1月18日ポッドキャスト · 2 人After a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the modelホスト 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.コーディングエージェント検索拡張生成（RAG）コンテキストエンジニアリング+3
1:53:08EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月18日ポッドキャストWhen GPT-4 Writes SQL, Four Tables Is the Breaking Pointホスト Nathan LabenzJuan Sequeda on why a knowledge graph is the accurate, explainable brain that foundation models do not have.RAG とナレッジKnowledge graphs検索拡張生成（RAG）+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
27:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年12月7日ポッドキャスト · 2 人Seven People Did the Work of 700. Salesforce's AI Chief Says Enterprise AI Is Still in the Second Inningホスト Sarah Guo, Elad GilClara Shih tells Sarah Guo and Elad Gil why Salesforce built a shared LLM platform, why data cleanup beats model shopping, and why AI is becoming the enterprise UI.企業と戦略エンタープライズ AIAI Strategy+3
1:32:40EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月31日ポッドキャストThe Historian Who Taught GPT-3.5 to Beat GPT-4ホスト Nathan LabenzMark Humphries on a kilometer of unread paper, fur-trade jargon that embeddings cannot see, and why cheap processing will force history to be rewritten.RAG とナレッジ検索拡張生成（RAG）ファインチューニング+3
1:26:30EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月24日ポッドキャストMost of this data has never been in a database: Chroma's wartime CTO on RAGホスト Nathan LabenzAnton Troynikov returns to The Cognitive Revolution to argue that retrieval quality is mostly the embedding, that Chroma should own the RAG loop, and that GPT still fails a basic Game of Life test of reasoning.RAG とナレッジ検索拡張生成（RAG）Embeddings+3
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月18日ポッドキャスト1,000 H100s Take 115 Days; 22,000 Take Fiveホスト Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.モデルと学習AI researchModel Interpretability+3
1:23:10EN
Cognitive Revolution "How AI Changes Everything"· 2023年9月19日ポッドキャストLuxury Purses Under $500 Beat a Bank's Fraud Modelホスト Nathan LabenzArthur.ai CEO Adam Wenchel on boundary attacks, LLM firewalls, and why a model that eats raw text cannot be secured from the inside.セキュリティと安全性AI securityPrompt injection+3
1:40:44EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月19日ポッドキャストGive the Model Time, Memory, and Tools: Nathan Labenz’s 2023 Field Guide to Using GPT-4ホスト Nathan LabenzPart two of the AI Scouting Report walks from H100 clusters and RLHF through chain-of-thought, retrieval, agents, and mixture-of-experts.エージェント検索拡張生成（RAG）Prompting & in-context learning+3
37:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年5月4日ポッドキャスト · 2 人Use Retrieval for a Wi-Fi Password. Use Experts for a Company's Private Language.ホスト Sarah Guo, Elad GilGoogle Brain's Kelvin Guu on REALM, FLAN, model surgery, and why personalizing large models is still an unsolved interface problem.RAG とナレッジ検索拡張生成（RAG）ファインチューニング+3
1:56:16EN
Cognitive Revolution "How AI Changes Everything"· 2023年4月6日ポッドキャストThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.ホスト 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.RAG とナレッジエージェント工学評価（Evals）+3
35:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年3月16日ポッドキャスト · 2 人Featured snippets stalled at 7%. A Google veteran used language models to hit 70%ホスト Sarah Guo, Elad GilNeeva founder Sridhar Ramaswamy tells No Priors why answers always beat links, why privacy never sold the switch, and why most queries do not need the biggest model.RAG とナレッジ検索拡張生成（RAG）Search & retrieval+3
1:44:19EN
Cognitive Revolution "How AI Changes Everything"· 2023年3月14日ポッドキャストTen People Versus Google’s $282 Billion Search Machineホスト Nathan LabenzPerplexity founder Aravind Srinivas tells Nathan Labenz why citations, speed, and value per minute — not chat bubbles — are how a tiny team competes with Google.プロダクトと UXAI startups & small teamsProduct Strategy+3
1:26:20EN
Cognitive Revolution "How AI Changes Everything"· 2023年3月2日ポッドキャストForty Dollars to Index Joe Rogan: Chroma, Shovels, and the Wright Flyer Era of MLホスト Nathan LabenzChroma co-founder Anton Troynikov on embeddings as the storage layer for language-model apps, Stable Attribution, and why machine learning is still flying on intuition.RAG とナレッジ検索拡張生成（RAG）Embeddings+3
2:24:31EN
Lex Fridman· 2019年10月11日ポッドキャスト · 2 人Watson Won Jeopardy Without Understanding. Ferrucci Wants AI That Can Explain Itselfゲスト David Ferrucci · ホスト Lex FridmanLex Fridman talks with David Ferrucci about IBM Watson, why prediction is not understanding, and why high-stakes decisions need machines that can reason with us.RAG とナレッジ検索拡張生成（RAG）AI research+3
1:22:36EN
Lenny's Podcastポッドキャスト · 2 人Stop Chasing AI News: Chip Huyen on What Actually Makes AI Products Betterゲスト Chip Huyen · ホスト Lenny RachitskyAuthor of AI Engineering walks through pre-training, post-training, RL, evals and RAG, then explains what separates companies that get value from AI from those that stall.プロダクトと UXファインチューニング検索拡張生成（RAG）+3
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