Mathematics, game playing, language and other high level behavior all emerge in human minds from more fundamental behaviors such as recognizing things via vision and other senses, positive and negative emotions that motivate behavior, and physical actions like speaking and moving. That is, human embryos go through stages in which they resemble the embryos of fish, amphibians, mammals and then primates. This classification is best explained by the kinds of games each is suitable for. Associationistic behavior is suitable for games such as naming the capitals of states. Complex-formal behavior is suitable for unsolved reasoning games, such as chess.
Nonformal behavior is suitable for ill-defined games such as riddles.
Dreyfus claims that the progress being made for the first three types of behavior is mostly useless for attacking nonformal behavior. Much recent artificial intelligence research is consistent with Dreyfus's ideas. The current emphasis is on machines that learn behaviors rather than machines whose behavior is precisely defined by complex sets of rules. It may be that machine intelligence will be created by combining sophisticated learning techniques with the enormous computing power of 100 billion neurons and 100 trillion synapses all working simultaneously. The laptop I got in 2000 has roughly 100,000 times the computing power of the minicomputer I used in 1968.