When you reach into a "statistical model" and find that it has generalized abstracts like "deceptive behavior", or "code error"? Abstracts that you can intentionally activate or deactivate - making an AI act as if 3+5 would return a code error, or as if dividing by zero wouldn't? That's abstract thinking.
Those are real examples of the kind of thing that can be found in modern production grade AIs. Not "anthropomorphizing" means not understanding how modern AI operates at all.
Almost all philosophy is incredibly worthless in general, and especially in application to AI tech.
Anything that actually works and is in any way useful is removed from philosophy and gets its own field. So philosophy is left as, largely, a collection of curios and failures.
Also, I would advise you to never discuss philosophy with an LLM. It might be a legitimate cognitohazard.
Those are real examples of the kind of thing that can be found in modern production grade AIs. Not "anthropomorphizing" means not understanding how modern AI operates at all.