alt Hacker NewsYou may be anthropomorphizing the model, here. Models don’t have “assumptions”; the problem is contrived and most likely there haven’t been many conversations on the internet about what to do when the car wash is really close to you (because it’s obvious to us). The training data for this problem is sparse.
I'd argue that "assumptions", i.e. the statistical models it uses to predict text, is basically what makes LLMs useful. The problem here is that its assumptions are naive. It only takes the distance into account, as that's what usually determines the correct response to such a question.