As I’ve mentioned elsewhere, not if by “information” you mean semantic content that a mind can process. What they have are vector fields (essentially just numbers) with statistically more or less likely relationships.
If I say, “take me out to the ballgame” to an LLM, the tokens representing the words in the next verse of the song are statistically “close” in the vector database, so it’s likely to generate them. But that doesn’t mean it actually knows the lyrics… or even has those lyrics recorded in a regular database anywhere.
That’s why they hallucinate. The model determines that the next token is something nonsensical, but it has no way of understanding that it has made a mistake. In a sense, it actually hasn’t made a mistake. It’s done exactly what it’s designed to do. It’s just that in the case of hallucinations, its output isn’t useful.