LLMs may kill genuine novelty

LLMs return the most probable continuation of existing text, trained on the past and answering with what is typical rather than what is true. The genuinely new is treated as a mistake, and feeding model outputs back as inputs narrows variance. Every major discovery was once out of distribution, but a consensus machine tells users the new thing is wrong.