Through Machine & Darkness  Video installation made using DCGAN trained on 45k Hubble Telescope ‘images’ (projection approx W3m), 35 minutes, looped. 

Programmer: Doug Neal. Scientific advice: STScI/NASA, USA.

Second development phase supported by Arts Council England Developing Your Creative Practice Grant (2019–21). Further information and experiments:

www.throughmachineanddarkness.co.uk

Developed as part of an artistic research project looking at the implications of the increasing use of AI and machine learning in examining astronomical datasets. This work comprises extracts from a DCGAN/neural network trained on 45k+ RAW images from the Hubble Space Telescope (HST). Attempting to conjure a total view of the cosmos, the imagery produced explored the latent space of the algorithmic imagination, as it learns to generate its view of the cosmos.