A common misconception: the space of possible intelligences is huge, and animal intelligence — the only kind humans have encountered — is one specific point arising from an optimization process that is fundamentally different from that driving current technologies.
Animal intelligence optimization pressure:
LLM intelligence optimization pressure:
Computational substrate (transformers vs. neural tissue), learning algorithms (SGD vs. unknowns), and implementation (episodic token processing vs.
continuously learning embodied self) differ — but most crucially, the optimization objectives differ.
LLMs are shaped far more by commercial selection than by biological evolution: less "tribal survival in the jungle," more "solve the task / get the upvote." These systems are humanity's first widespread contact with non-animal forms of intelligence, though they remain entangled with human artifacts.
Some have proposed names like "ghosts" or "spirits" to highlight that distinction.
Those who form accurate internal models of this new kind of intelligence will be better positioned to reason about and predict its behaviors.
Those who continue to think of it purely as an animal-like mind will be prone to systematic misunderstandings