Will machines one day be as creative as humans? - Microsoft Research

Recent methods in artificial intelligence enable AI software to produce rich and creative digital artifacts such as text and images painted from scratch. One technique used in creating these artifacts are generative adversarial networks (GANs). Generative adversarial networks are a recent breakthrough in machine learning. Initially proposed by Ian Goodfellow and colleagues at the University of Montreal at NIPS 2014, the GAN approach enables the specification and training of rich probabilistic deep learning models using standard deep learning technology. Allowing for flexible probabilistic models is important in order to capture rich phenomena present in complex data.