The lecture gives an introduction to neural networks and how they work, with strong focus on Convolutional Neural Networks, which are mainly used for image recognition and image sythesis tasks. Instead of going into the mathematical details, we try to learn common concepts like backpropagation and activation functions as pictorial as possible. Different network types and architectures are shortly explained and accompanied with examples that have their origin in the field of art.

Instead of predicting the doomsday future of human creativity, the main idea is to show the potential this new technology has.