LLM weights are frozen once the model is trained and a specific version is released, or this is true at least currently for almost all major models. You can ask interesting consciousness questions about LLMs, but you most definitely need to separate LLMs during training (whether this is pre-training, later fine-tuning, or general instruction tuning approaches) and after, during inference. None of this has any relevance to the core points I was making re: useful vs. useless discussions of LLMs and consciousness, because the weights point was just a minor example to illustrate a larger point about how narrowing the scope of the conversation is necessary for productive discourse.

I doubt we agree on what "rigorous definitions" means, given that you are happy to continue using a useless, vague family resemblance concept like "consciousness", but complain that pointing out dynamicness and/or change is involved is too vague.

I believe one cannot give a rigorous definition of consciousness precisely because it is a family resemblance concept, and there is no actual essence. This is why I suggest shifting to talking about aspects, since then productive insights and truths can be discovered.