I am using large language models (LLMs) like GPT-3.5 and GPT-4, and others.
While going through various materials, I came across the term "knowledge base" which seems to be used in conjunction with these models. However, I am a bit puzzled about what exactly a knowledge base refers to.
From what I understand, a knowledge base in general terms refers to a collection of structured or unstructured data that can be leveraged for information retrieval or problem-solving.
However, when mentioned alongside LLMs, does it have a specific meaning or structure?
Does it refer to a continuously updated source of information that the model can access to provide more accurate or up-to-date responses?
Moreover, how does a knowledge base interact with a large language model, and what benefits does it provide in enhancing the model's capabilities?
Could someone shed some light on this or point me to relevant resources to better understand the concept of a knowledge base in the context of large language models?