I am still not sure but after seeing Schmidhuber's talk last week, I think it is being able to find regularities/patterns, resulting in a compressed representation that allows to understand and compress some aspect of the world, and building layers (abstractions) of those compressed representations. This allows you to navigate through very large search spaces much much faster.
It's a fascinating subject, and at the core of what we are. I recommend the film.
https://en.wikipedia.org/wiki/The_Man_Who_Knew_Infinity_(fil...
You don't need to explain every dendritic cluster in order to extract core, composable and generative abstractions useful enough to shorten time to understanding by orders of magnitude (discovery of zero vs how quickly it can be taught).
A large part of human success is that we are able to transmit knowledge to each other and accumulate experience over generations. A human starting from scratch is not very much more than its ape cousins.
Human beings can explain efficiently because we must learn concepts decomposably and can take deductive shortcuts. In its purest form we have mathematical proofs as explanations. Explanations work with core concepts and generates on that basis. E.g. We want to know A and we know B, B is applicable in condition C. We will show condition C applies. With B, A can be shown in terms of...
When you give big data to machines they work with raw correlations and output predictions. But humans have to be more creative because our scratch space is so small. Newton took Brahe's big data and compressed it to a theory of universal gravitation. Darwin made a relatively small number of observations, all things considered, and came up with On the Origin of Species.