Earlier quoted context omitted.
AI safety research posits that there are certain goals that will always be wanted by any sufficiently smart AI, even if it doesn't understand them anything close to like a human does. These are called "instrumental goals", because they're prerequisites for a large number of other goals[0]. For example, if your goal is to ensure that there are always paperclips on the boss's desk, that means you need paperclips and so…
There is a whole theoretical justification behind instrumental convergence that you are handwaving over here. The development of instrumental goals depends on the entity in question being an agent, and the putative goal being within the sphere of perception, knowledge, and potential influence of the agent. An LLM is not an agent, so that scotches the issue there.
See also: https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_wha...
See also: evolution - the OG case of a strong optimizer that is not an agent. Arguably, the "goals" of evolution are the null case, the most fundamental ones. And if your environment is human civilization, it's easy to see that money and compute are as fundamental as calories, so even near-random process should be able to fixate on them too.