I am very dummy on LLMs, but wouldn't a confined model (no internet access) eventually just loop to repeating itself on each consecutive run or is entropy enough for them to produce endless creativity?
High temperature settings basically make an LLM choose tokens that aren’t the highest probability all the time, so it has a chance of breaking out of a loop and is less likely to fall into a loop in the first place. The downside is that most models will be less coherent but that’s probably not an issue for an art project.
I think the model being fixed is a fascinating limitation. What research is being done that could allow a model to train itself continually? That seems like it could allow a model to update itself with new knowledge over time, but I'm not sure how you'd do it efficiently
In order to make this probability distribution useful, the software chooses a token based on its position in the distribution. I'm simplifying here, but the likelihood that it chooses the most probable next token is based on the model's temperature. A temperature of 0 means that (in theory) it'll always choose the most probable token, making it deterministic. A non-zero temperature means that sometimes it will choose less likely tokens, so it'll output different results every time.
Hope this helps.