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• Advanced RAG; Chunking, Embeddings, and Vector Databases

Advanced RAG; Chunking, Embeddings, and Vector Databases

Abstract

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.

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