Large Language Model’s don’t really have a database to query on. They analyse petabytes of data on a range of topics (as part of “training”), and measure the distance between clusters of words or pixels that are most likely to appear together. They then match the pattern to a given natural language prompt, and generate a remixed output in the form of text or image. It is generally a learnt synthesis of the kind of content or image that has been created before on the subject of the prompt.

The output depends on what you ask (hence prompt engineering), but in most cases a basic human language query is enough for the system to match patterns and return some text or image which looks good and reads ok.

Question though, is novelty aside, what do you ask a system that (apparently) can answer anything? Where does it truly help beyond writing content or creating images?