Can meaningful value exist in AI-generated text regardless of its origin?

The paper has an LLM generate a fictional Buddhist sutra and analyzes it philosophically and literarily. Its conceptual subtlety, rich imagery, and density of allusion make the text hard to dismiss merely because of its mechanistic origin — and the authors conclude that meaning and value can be ascribed to it. The crucial move is a careful separation: the claim is not about where meaning comes from (the human prompter, the humans whose writing trained the model, or the readers who interpret it) but only that meaning and value can be discerned in what was produced. Discernibility is decoupled from source.

That separation is the keeper. The familiar deflationary objection — "the meaning is really the user's / the training data's / the reader's, not the model's" — does not touch the weaker, sufficient claim that meaning is present and readable. And that weaker claim is enough to raise the unsettling possibility: a technology that encroaches on human meaning-making across social relations, the arts, and religion.

This is a direct contribution to Adrian's meaning thread. It sits in productive tension with How does AI-generated false experience differ linguistically from human deception? — that note locates a category of AI text that lacks a truth-grounding, while Xeno Sutra locates a category where value is nonetheless discernible — and it extends How do readers actually build meaning from words?: if meaning is resonance detected by a reader, then it can be discerned in AI text regardless of how the text was produced, which is precisely the paper's claim. It complements Is the LLM a tool or a new form of intelligence itself? by asking what value a medium's output can carry when no author stands behind it.