A financial services company wants to build an internal chatbot for its investment advisors. The chatbot must answer questions about current market conditions and breaking financial news. A critical requirement is that all information provided must be traceable to specific, up-to-the-minute financial reports and news articles stored in a constantly updating database. Which strategy for adapting a pre-trained language model would be most effective and efficient for this specific use case?

A development team is deciding how to adapt a large language model for a new application. They are considering two primary methods. Match each characteristic or requirement to the most suitable adaptation method described below.

Method A: Modifying the model's internal parameters by training it on a curated dataset of examples. Method B: Augmenting the model's input with relevant information retrieved from an external knowledge base at the time of the query.

Choosing an LLM Adaptation Strategy for a Creative AI Assistant