Optimizing Chunking for Effective Conversational AI Retrieval

This presentation explores chunking, a crucial technique in RAG systems and conversational AI, detailing its definition, importance, and applications. It examines key parameters like chunk size, overlap, and context retention, and delves into common strategies such as fixed-size, recursive, and semantic-based chunking. The discussion highlights the significance of proper chunking for improving retrieval accuracy and system performance. Attendees will gain actionable insights and best...