





Manipulated Network: quirks and oddities from corrupted generative models
Type
Algorithmic Digital Images
Materials
TensorFlow, generative adversarial networks, 29.7 x 21 cm canvas
Mar, 2022
During the re-implementation of Network Bending, I’ve come across plenty of quirks and oddities generated from corrupted models. These models produce impossible, distorted but realistic images, diverted from the original outputs and sometimes lead to aesthetic preoccupations. Although utilising machine autonomous, creating this collection is still like a craft: I marked configurations that cause these semantically meaningful results, tweaked and built the operation template again, and then re-examined the subsequent images.
The decisions can be either arbitrary or intentional, sometimes deliberate, all in order to create potentially aesthetic results.