Noise through to twos and sevens: creating audiovisual artworks from artificial neural networks' processing data

This piece is the result of the sonification and visualization of an artificial neural network’s processing data. At its core, it is an attempt at making art from artificial intelligence with a non-generative approach, leaving all creative agency to the artist; at exploring structures inherent to the operation of neural networks; at commenting on the nature of these ubiquitous, yet notoriously unintelligible algorithms. It does so by focusing on some of the network’s internal data streams during training, looking at their gradual movement from noise to order, and mapping this information onto sound and visual materials and processes derived from ‘glitch’ and drone traditions, that offer interesting aesthetic parallels to this evolution of the data.