Your definition of "learning" is incomplete because you're applying LLM concepts to how human brains work. An LLM only "learns" during training. From that point forward all it has is its context and vector DBs. If an LLM and vector DB is not actively interacted with, nothing happens to it. However for the brain, experiencing IS learning. And the brain NEVER stops experiencing.

Just because I don't remember my experiences at second 45232 on May 22, doesn't mean that my brain was not actively adapting to my experiences at that moment. The brain does a lot more learning than just what is conscious. And then when I went to sleep the brain continued pruning and organizing my unconscious learning for the day.

Seeing if someone can go from token to freeform physical usefulness will be interesting. I'm of the belief that LLMs are too verbose and energy intensive to go from language regurgitation machines to moving in the real world according to free form prompting. It may be accomplishable with the vast amount of hype investment, but I think the energy requirements and latency will make an LLM-based approach economically infeasible.