  Computational complexity has often been ignored in philosophy of mind, in
philosophical artificial intelligence studies. The purpose of this paper is
threefold. First and foremost, to show the importance of complexity rather than
computability in philosophical and AI problems. Second, to rephrase the notion
of computability in terms of solvability, i.e. treating computability as
non-sufficient for establishing intelligence. The Church-Turing thesis is
therefore revisited and rephrased in order to capture the ontological
background of spatial and temporal complexity. Third, to emphasize ontological
differences between different time complexities, which seem to provide a solid
base towards better understanding of artificial intelligence in general.
