LLM Optimization: Best Practices for Choosing Between RAG and Fine-Tuning

This roundtable on LLM Optimization brings together leading experts in the field to delve into the best practices for choosing between Retrieval-Augmented Generation (RAG) and fine-tuning methods. Attendees will gain insights into the nuances of each approach, exploring how RAG can enhance model responses with external data retrieval and how fine-tuning can tailor models to specific tasks or datasets. The session aims to provide a deep understanding of these techniques, their applications, and the decision-making criteria for selecting the most suitable method for various enterprise needs. This discussion is crucial for professionals looking to harness the full potential of large language models in their operations.