筛选结果
13 篇排序
1:35:29ENUber Burned a Year of Tokens in 13 Weeks. Retrieval Is How Agents Win主持 Nathan LabenzMongoDB Field CTO of AI Pete Johnson argues that agent performance now hinges on retrieval quality, not on stuffing million-token context windows.
1:29:02ENShe Never Sees a Row of Your Data. The Answers Still Clear 95%.主持 Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.
1:21:53ENHippoRAG Matches Iterative Retrieval at One-Tenth the Online Cost主持 Nathan LabenzA hippocampus-inspired knowledge graph lets multi-hop questions skip the brute-force document crawl.
1:25:10ENA Tenth of Google's Index, 99.9% Recall: How 20 People Built Brave Search主持 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.
1:27:01ENThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG Playbook主持 Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.
1:23:09ENThe Right Size of an AI Task Is Whatever You Can Check主持 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.
Google Gives You 33 Million Results. Exa Wants 54.主持 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.
1:53:08ENWhen GPT-4 Writes SQL, Four Tables Is the Breaking Point主持 Nathan LabenzJuan Sequeda on why a knowledge graph is the accurate, explainable brain that foundation models do not have.
1:32:40ENThe Historian Who Taught GPT-3.5 to Beat GPT-4主持 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.
1:26:30ENMost of this data has never been in a database: Chroma's wartime CTO on RAG主持 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.
1:56:16ENThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.主持 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.
1:26:20ENForty Dollars to Index Joe Rogan: Chroma, Shovels, and the Wright Flyer Era of ML主持 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.
1:06:22ENPerplexity's Bet: Search Becomes Answers, and Answers Become a Business主持 Jacob EffronThe Perplexity CEO explains how a consumer AI search product is built, sequenced, and defended against Google.









