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Matthew Berman昨日 +13AI Engineer昨日 +6Theo - t3․gg昨日The Builders昨日 +1a16z昨日 +2硅谷101昨日 +1SemiAnalysis昨日 +1Chris Williamson昨日Cheeky Pint昨日Invest Like The Best昨日

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62 件
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トピック検索拡張生成（RAG）
1:27:01EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月8日ポッドキャストThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG Playbookホスト Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.RAG とナレッジ検索拡張生成（RAG）Vector search+3
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
スライド 3 枚12:15EN
Matthew Berman· 2023年11月21日Build a Video-Transcript Chatbot with MindStudioMatthew Berman · Forward FutureIn a sponsored 2023 tutorial, Matthew Berman builds a no-code retrieval workflow that answers questions about one of his videos.検索拡張生成（RAG）Workflow automationAI agents
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
スライド 6 枚9:55EN
Matthew Berman· 2023年7月14日Building AI Characters With the a16z Companion AppMatthew Berman · Forward FutureMatthew Berman walks through a 2023 starter project for conversational characters, from service configuration and embeddings to editing a companion’s personality.AI agentsSoftware engineering検索拡張生成（RAG）+1
54:00EN
20VC with Harry Stebbings· 2023年6月30日ポッドキャスト · 2 人Douwe Kiela on Data, Retrieval and Enterprise AIゲスト Douwe Kiela · ホスト Harry StebbingsThe Contextual AI CEO discusses language model trade-offs, evaluation, open models and the hurdles to enterprise use.エンタープライズ AI検索拡張生成（RAG）Data quality & curation+2
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
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