Obviously LLMs aren't deterministic, but they generally can be modeled as a simple, stateless, function: Given text, generate text. Depending on your views towa

Obviously LLMs aren't deterministic, but they generally can be modeled as a simple, stateless, function: Given text, generate text. Depending on your views towards wasting energy, why store something that can be "trivially" re-generated? One reason to NOT want to persist an LLM output is to avoid contaminating the internet with LLM text that could be confused for human text. This is useful for historical reasons (what did people say/think) and for future LLM training purposes. In the future, there might be other reasons to not persist LLM-generated text. If you store the inputs instead of outputs then it can be "replayed" with a new LLM. I can generate some text via an LLM running on my phone, but if I later wanted a higher-quality output, it'd be easier to re-generate the data on my laptop later (or the cloud, obviously). One related idea that comes to mind is personalization - let the LLM use language each reader is familiar with, or focusing on different bits of info to different people. Maybe if an LLM knows I have a PhD in a certain subject, it'd summarize a research paper differently than it'd summarize it for my neighbor who has different preexisting knowledge.