Unlocking the Power of Large Language Models: Challenges and Considerations of Retrieval-Augmented Generation in the Power Sector
, Principal Technical Leader, EPRI
Retrieval-augmented generation (RAG) has become the biggest use case for large language model (LLM)-powered chatbots, a paradigm that offers updating of an LLM’s knowledge base and mitigates its hallucinations. We'll cover foundations of the RAG architecture, including key considerations and optimization techniques as they apply in the power sector. We'll explore the importance and challenges in performance evaluations, issues in deployment, and the pitfalls and inherent limitations of building RAG systems. We'll conclude by discussing topics beyond RAG, and other possible innovative applications of LLMs in the energy sector.