Blade Runner – Autoencoded (2016, 10 min) 25 October 2018

autoencodingbladerunner

Blade Runner—Autoencoded is a film made by training an autoencoder—a type of generative neural network—to recreate frames from the 1982 film Blade Runner. The Autoencoder learns to model all frames by trying to copy them through a very narrow information bottleneck, being optimized to create images that are as similar as possible to the original images. The resulting sequence is very dreamlike, drifting in and out of recognition between static scenes that the model remembers well, to fleeting sequences—usually with a lot of movement—that the model barely comprehends. By reinterpreting Blade Runner with the autoencoder’s memory of the film, Blade Runner—Autoencoded seeks to emphasize the ambiguous boundary in the film between replicant and human, or in the case of the reconstructed film, between our memory of the film and the neural networks.

About the artist

Terence Broad (GB) is an artist and researcher based in London. He is currently pursuing a PhD at Goldsmiths, University of London. His work has been exhibited internationally at venues including The Garage Museum of Contemporary Art, The Barbican and The Whitney Museum of American Art.

This film is part of

Automating Cinema

Other films in this program