What I'm warning is against thinking of them as independent agents with their own minds, because they don't work like that at all, so you'd be anthropomorphising them.
These models certainly have a compilation of knowledge, but it is statistical knowledge - in the same way as a book of logarithms has lots of mathematical knowledge, but you wouldn't say that the book 'knows logarithms'. The compilation contains statistical 'truths' about the topics on which it has been trained; and contrary to a written book, that knowledge can be used operationally to build new information.
Yet that static knowledge does not reach the point of having a will of its own; there is nothing in the content generation system that makes it take decisions or establish its own objectives from its statistical tables of compiled knowledge.
We fall for it because normally the use of language is an expression of something, with ChatGPT language is just that, language, with no meaning. To me that proves knowing and reasoning happens on a deeper, more symbolic level and language is an expression of that, as are other things.
It's better to think of this models as 'generating' chains of relevant words, where 'relevant' is defined by similarity of those areas of knowledge on which it has been trained, and which are "activated" as close to the topics in the prompt. Which is not at all dissimilar to how humans learn about a new topic, btw.
This way, by "activating" concepts of areas of knowledge and finding words that are more likely than others to fit those concepts, the model is able to create texts following the constraints you instruct it with - such as poems that rhyme, or critical analysis of scientific articles.
The most important point to be aware of is that this creation model is completely different to how automatic reasoning models create content, which is by having a formal representation of a knowledge domain and creating logical inferences that can be mathematically proven correct within the model. A reasoning model cannot lie, but it cannot create content beyond the logical implications of its premises; its quite the opposite of what language models do.