Tailoring large language models for specific energy domains

Large language models (LLMs) excel in diverse tasks due to their broad training. However, their general-purpose nature can hinder their performance in specialized energy domains, where handling sensitive and domain-specific information is crucial. The vast technical jargon and unique language across energy disciplines pose a challenge. To unlock the full potential of LLMs in these specialized areas, targeted adaptation strategies are essential.