Advanced RAG: Chunking, Embeddings, and Vector Databases 🚀

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.