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Advanced RAG: Chunking, Embeddings, and Vector Databases 🚀 | LLMOps

In this talk, Yujian from Zilliz talked about advanced RAG concepts including Chunking, Embeddings, and Vector Databases in RAG (Retrieval Augmented Generation) models Topics that were covered: ✅ Chunking: Understand the concept of chunking and its role in improving the efficiency of information retrieval. Learn how to implement chunking in RAG to optimize the retrieval of relevant information. ✅ Embeddings: Dive into the world of embeddings, a method used to represent text as vectors. Discover how to enhance the performance of RAG models by enabling more accurate and efficient information retrieval. ✅ Vector Databases: Explore the use of vector databases in storing and managing embeddings. Learn how to leverage vector databases to speed up the retrieval process in RAG models. About LLMOps Space - LLMOps.Space is a global community for LLM practitioners. 💡📚 The community focuses on content, discussions, and events around topics related to deploying LLMs into production. 🚀 Join discord: https://llmops.space/discord