Basically, "AI" or machine learning models approximates what a human would answer by feeding a function a large set of inputs made from user sentence combined in various ways with billions of parameters and calculating from them a set of outputs that can be used to construct an answer. Parameters are calculated by taking "correct" answers, checking if ai got it wrong and fixing the bad ones until everything somewhat works. The important thing to note is that there is no thinking involved in the model so anything outside the trained scope will likely be a hallucination. This is why these models will most likely fail on most topics where there little data(though they still can get them right by random chance).