That's a bad analogy, none of those things are emergent behavior.
We can debate whether what an llm does is "emergent" - it's basically a definition thing though and isn't very interesting.
In reality, what's most surprising is that so much of what we say is explainable as next token prediction. It's not the other way around - we're showing how predictable we are, rather than how smart the AI is. But it's clear to me that it's in the outlying cases where the differences are. AI doesn't extrapolate outside it's training data, and even if it gets (100-\alpha)% of it's output right, there is always some alpha that's not in the training data and differentiates pattern matching or fancy key-value lookup (which is how we know AI works) from whatever intelligence is.