

That depends on what you mean by “know.” It generates text from a large bank of hopefully relevant data, and the relevance of the answer depends on how much overlap there is between your query and the data it was trained on. There are different models with different focuses, so pick your model based on what your query is like.
And yeah, one big issue is the confidence. If users are aware of its limitations, it’s fine, I certainly wouldn’t put my kids in front of one without training them on what it can and can’t be relied on to do. It’s a tool, so users need to know how it’s intended to be used to get value from it.
My use case is distilling a broad idea into specific things to do a deeper search for, and I use traditional tools for that deeper search. For that it works really well.
Why not? It’s basically a search engine for whatever it was trained on. Yeah, it’ll hallucinate sometimes, but if you’re planning to verify anyway, it’s pretty useful in quickly distilling ideas into concrete things to look up.