It's not enough to emulate the properties of intelligence, you have to emulate the reason for there needing to be intelligence in the first place.
This difference was clear to me when reading up on existing AI and machine learning methods.
AI in it's current form feels more like engineering than an exploration in nature, science and math. Slightly dangerously with my limited knowledge in AI i would describe AI today as an extremely useful and insightful set of tools inspired by nature, but which are not themselves nature. They are just yet another thing that we have learnt to re-implement as a fruit of biology. Actually cellular automata feel more like nature than AI.
Methods such as neural networks are pre-evolved static solutions, the information flowing through them may evolve, but the method which determines their flow does not itself evolve, they are therefore selective and static imitations of the a brain much the same as an animatronic manikin is an imitation of the body at an evolutionary static point in time.
It's conceivable that with enough detailed imitation an intelligent implementation of a whole brain (not even human) could be achieved... but it seems highly unlikely and impractical. However implementing the basis or conditions to give emergent and undirected development in a "synthetic" medium would be nature at work or "life" in my view. Imagine an AI that had the freedom and incentive to create it's own methods dynamically, that kind of creative freedom must be a pretty good fit for true "Artificial Life", so shouldn't it be called "Emergent Intelligence"... The opposite to "Imitated Intelligence".