30 2 What Is Human-Like General Intelligence? between the learning components associated with different kinds of memory, and hence are un- likely to give rise to the emergent structures and dynamics characterizing general intelligence. One of the central ideas underlying CogPrime is that with an integrative cognitive architecture that combines multiple aspects of intelligence, achieved by diverse structures and algorithms, within a common framework designed specifically to support robust synergetic interactions between these aspects. The simplest way to create an integrative AI architecture is to loosely couple multiple com- ponents carrying out various functions, in such a way that the different components pass inputs and outputs amongst each other but do not interfere with or modulate each others’ internal functioning in real-time. However, the human brain appears to be integrative in a much tighter sense, involving rich real-time dynamical coupling between various components with distinct but related functions. In [Goe09a] we have hypothesized that the brain displays a property of cognitive synergy, according to which multiple learning processes can not only dispatch subproblems to each other, but also share contextual understanding in real-time, so that each one can get help from the others in a contextually savvy way. By imbuing AI ar- chitectures with cognitive synergy, we hypothesize, one can get past the bottlenecks that have plagued AT in the past. Part of the reasoning here, as elaborated in Chapter 9 and [Goe09b], is that real physical and social environments display a rich dynamic interconnection between their various aspects, so that richly dynamically interconnected integrative AI architectures will be able to achieve goals within them more effectively. And this brings us to the patternist perspective on intelligent systems, alluded to above and fleshed out further in Chapter 3 with its focus on the emergence of hierarchically and heterarchi- cally s