Large language model (LLM) applications are essential in enhancing productivity across industries through natural language. However, their effectiveness is often limited by the extent of their training data, resulting in poor performance when dealing with real-time events and new knowledge the LLM isn��t trained on. Retrieval-augmented generation (RAG) solves these problems.
]]>