The phenomenon of intelligence still raises fascinating questions. Hence studying it means entering unknown depths and constantly giving rise to new disciplines. Perhaps the attraction of the phenomenon stems precisely from the fact that numerous mysteries still seem unsolved: We are left with the phenomenon itself. Nevertheless, in the research field of AI, efforts are being made to thoroughly assess and even replicate the phenomenon by technical means. Historically and methodologically, two different approaches are opposed to one another, reflecting the dichotomy of mind and brain: The initially dominant symbolic approach to AI attempts to capture the phenomenon of the mind by logically representing world knowledge, ontologically relating it, and automatically reasoning on its basis. In contrast, today’s dominant sub-symbolic AI intends to bionically mimic the human brain with artificial neural networks that sense the world and learn from it through data.