The talk presents briefly the main principles used in AI, from Aristotle’s true/false logic, through fuzzy logic, evolutionary computation and neural networks, to arrive at the current state-of-the-art in AI – the deep learning machines. One particular such machine, developed in the presenter’s KEDRI Institute and dubbed NeuCube, is designed for deep learning of complex data patterns so as to predict future events. It uses the latest AI technique called spiking neural networks (SNN) that mimics the learning capabilities of the human brain. NeuCube has already demonstrated its usefulness when dealing with Big Data such as brain EEG and fMRI data; brain-computer interfaces; seismic data; and environmental data for stroke prediction. This is the beginning of understanding complex patterns of changes of variables in space and time and their relevance to future events. It will have a significant impact on our understanding of the dynamics of the micro and the macro worlds with particular application in medicine.