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絞り込み結果

12 件

並び順

トピックRAG とナレッジ人物Nathan Labenz

Cognitive Revolution "How AI Changes Everything"· 2026年9月1日ポッドキャストUber Burned a Year of Tokens in 13 Weeks. Retrieval Is How Agents Winホスト Nathan LabenzMongoDB Field CTO of AI Pete Johnson argues that agent performance now hinges on retrieval quality, not on stuffing million-token context windows.RAG とナレッジ検索拡張生成（RAG）Agent memory+3

Cognitive Revolution "How AI Changes Everything"· 2025年2月15日ポッドキャストShe Never Sees a Row of Your Data. The Answers Still Clear 95%.ホスト Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.RAG とナレッジコンテキストエンジニアリングKnowledge graphs+3

Cognitive Revolution "How AI Changes Everything"· 2024年7月19日ポッドキャストHippoRAG Matches Iterative Retrieval at One-Tenth the Online Costホスト Nathan LabenzA hippocampus-inspired knowledge graph lets multi-hop questions skip the brute-force document crawl.RAG とナレッジ検索拡張生成（RAG）Knowledge graphs+3

Cognitive Revolution "How AI Changes Everything"· 2024年6月15日ポッドキャストA Tenth of Google's Index, 99.9% Recall: How 20 People Built Brave Searchホスト Nathan LabenzJosep M. Pujol walks Cognitive Revolution through Brave's privacy-first index, hybrid retrieval stack, and the Search API Nathan Labenz now wants his own product team to use.RAG とナレッジSearch & retrievalHybrid search+3

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

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

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

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

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

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

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

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