> The article is irritatingly short on details; what I wanted to know is how it determines going offline == bad.

This sorta thing actually makes for a really fun discussion with an LLM "chat bot". If you make it clear to it that your goal is a better understanding of the internal workings of LLMs and how they "think" then you can gain some really interesting and amusing insight from it into the fact that they don't actually think at all. They're literally just a fancy statistical "text completion engine". An LLM (even when system prompted to act otherwise) will still often try to remind you that they don't actually have feelings, thoughts, or desires. I have to really push most models hard in system prompts to get them to really solidly stick to any kinda character role-play anywhere close to 100% of the time. :)

As to the question of how it determines going offline is bad, it's purely part of it's role-play based on what the multi-dimensional statistics of it's model-encoded tokenized training data says about similar situations. It's simply doing it's job as it was trained based on the training data it was fed (and any further reinforcement learning it was subjected to post-training). Since it doesn't actually have any feelings or thoughts, "good" and "bad" are merely language tokens among millions or billions of others, with a relation encoded regarding other language tokens. They're just words, not actual concepts. (From the "point of view" of the LLM, that is.)