In my experience, they contain more information than any human but they are actually quite stupid. Reasoning is not something they do well at all. But even if I skip that, they can not learn. Inference is separate from training, so they can not learn new things other than trying to work with words in a context window, and even then they will only be able to mimic rather than extrapolate anything new.
It's not the lack of perfect, it's the lack of reasoning and learning.
I've seen a lot of reasoning in the latest models while engaging in agentic coding. It is often decent at debugging and experimentational, but around 30% it goes does wrong paths and just adds unnecessary complexity via misdiagnoses.