The Hitchhiker’s Guide to Productionizing Retrieval 🤖 This is a must-read starter by @itsclelia, in partnership with @qdrant_engine, for anyone looking to build a RAG/retrieval pipeline for your AI agents. It contains practical tips and reference repos 📚 for every stage of the https://x.com/jerryjliu0/status/1945647281782636974
Announcing a new Coursera course: Retrieval Augmented Generation (RAG) You’ll learn to build high performance, production-ready RAG systems in this hands-on, in-depth course created by https://x.com/AndrewYNg/status/1945502636012445937
We’re thrilled to announce our new course: Retrieval Augmented Generation (RAG) RAG is a key part of building LLM applications that are grounded, accurate, and adaptable. In this course, taught by AI engineer @ZainHasan6 and available on @Coursera, you’ll learn how to design https://x.com/DeepLearningAI/status/1945506275481022872
all modality RAG 🔥 ColQwen-Omni is a new multimodal retrieval model that can retrieve anything (videos, audios, documents and more!) use with transformers 🤗 here’s a smol demo on video retrieval ↙️ https://x.com/mervenoyann/status/1945862039022207386
RT @ManuelFaysse: Introducing ColQwen-Omni, a 3B omnimodal retriever that extends the ColPali concept of multimodal retrieval with late int…”” / X https://x.com/andersonbcdefg/status/1945855681976021268
RT @bibryam: RAG Patterns more resources: https://x.com/rachel_l_woods/status/1944206536424739230
Kohere! 🇰🇷 Were very excited to be opening our first office in Asia in Seoul. 저희는 테크 및 세일즈 분야에서 채용 중이며, 한국 기업들이 AI 기술을 도입하여 성장하고 번영할 수 있도록 돕는 일에 매우 기쁩니다!”” / X https://x.com/aidangomez/status/1944913553640558638
LLMs often botch private graph QA because a single bad link breaks the path. BYOKG-RAG (“bring-your-own” Knowledge Graph) fixes that by having the model suggest entities, paths, and Cypher, then letting specialised tools retrieve real graph chunks and feeding them back for one https://x.com/rohanpaul_ai/status/1945822543182709243
