"Minimize training loss while isolated from the environment" is not at all similar to "maximize replication of genes while physically interacting with the environment". Any human-like behavior observed from LLMs is built on such fundamentally alien foundations that it can only be unreliable mimicry.
The environment for the model is its dataset and training algorithms. It's literally a model of it, in the same sense we are models of our physical (and social) environment. Human-like behavior is of course too specific, but highest level things like staged learning (pretraining/posttraining/in-context learning) and evolutionary/algorithmic pressure are similar enough to draw certain parallels, especially when LLM's data is proxying our environment to an extent. In this sense the GP is right.