Enhancing AI with Synthetic Data

This chapter explores the impact of synthetic data on improving Retrieval-Augmented Generation (RAG) and large language models. It discusses the methodologies for training models with synthetic data and how it can elevate model performance while addressing concerns about quality and model collapse. The dialogue further examines the future of RAG and the transformative potential of automating data processing through intelligent agents.