The difference is quantitative, rather than qualitative, as compared to primitive Markov models that have been used in the past. It's just a numerical model wi

The difference is quantitative, rather than qualitative, as compared to primitive Markov models that have been used in the past. It's just a numerical model with a very large number of parameters that extends a text token sequence. The parameter size is so large that it has in essence memorized its training data, so if the right answer was already present in the training data you'll get it, same if the answer is closely related to the training data in a way that lets the model predict it. If the wrong answer was present in the training data you may well get that.