> Oxford Dictionary says "the ability to acquire and apply knowledge and skills". And what is knowledge? When I say I know p, then p is a proposition. Thus, p

> Oxford Dictionary says "the ability to acquire and apply knowledge and skills". And what is knowledge? When I say I know p, then p is a proposition. Thus, p is intelligible. Anything intelligible is conceptual. Indeed, if we analyze what a proposition is, we see that it entails predicates and predicates correspond to concepts. However, concepts are abstract and universal, that is, they are not concrete or particular, they are not mere images. Triangularity is not this or that triangle, but that which holds of all triangles, and you will not find triangularity out and about in the world on its own, but only instantiated in particulars, and any particular is not any of the other particulars for which the same predicate holds. When we implement propositions in computers, we really only simulate the formal via mechanical manipulations. When I create a negation operation on a string of symbols, I am only moving symbols around in a way that corresponds to what negation would produce. But the computer is not strictly speaking negating anything. Furthermore, the symbols that stand for predicates are just placeholders at best. There is no concept in the machine. Deep learning does not somehow magically transcend this limitation. > "The ability to create models of the world around them, and make predictions based on those models" Modeling and prediction is not intelligence, but a consequence of it. It is also central to modern science because the purpose of modern science is, to a large degree, less about understanding nature than it is about mastering it for practical purposes (prediction is presupposed by control).