Art and Machine Learning

Catalog description

Artistic creation and neural networks have been rubbing shoulders for a long time, but today we are witnessing an explosion of interest in machine learning and aesthetics. Many of the tasks that machine learning models face today are aesthetic tasks, ranging from the classification of images (CNNs) to the generation of completely new images (GANs). At the same time, the technical opacity of machine learning models makes it difficult to properly evaluate their results. The once speculative question "how does the machine perceive the world" has become a real-world problem. This class provides a high-level introduction to the aesthetics, politics, and epistemology of machine learning, combining the close reading of texts and source code alike.