Zabludowicz Collection presents CUSP, an Invites exhibition by London-based artist Jake Elwes.
CUSP is a new work which explores the intersection between nature and machine and the interplay between two realities: one generated by human perception and experience, and the other generated by artificial intelligence. In CUSP, 2019, Elwes reframes a familiar childhood location on the Essex marshes by inserting images randomly created by a neural network (GAN*) into this tidal landscape.
Initially trained on a photographic dataset, the machine proceeds to learn the embedded qualities of different marsh birds, in the process revealing forms that fluctuate between species, with unanticipated variations emerging without reference to human systems of classification. Elwes has actively selected a series of images from among those conceived by the neural network, and then combines these together into a single animation that migrates from bird to bird, accompanied by a soundscape of artificially generated bird song. The final work records these generated forms as they are projected, using a portable perspex screen, across the mudflats in Landermere Creek. The work both augments and disrupts the natural ecology of the location, as flocks of native birds enter a visual dialogue with these artificial ones.
Jake Elwes (b. 1993, London, UK) received his BA Fine Art from Slade School of Fine Art, UCL in 2017, with a year spent at SAIC, Chicago. His recent works focussed on the technological and cultural developments of Artificial Intelligence have been exhibited widely including Bloomberg New Contemporaries, 2017 in Newcastle and London UK; Ars Electronica, 2017, Linz, Austria; Centre for Future Intelligence, 2017, Cambridge, UK; Victoria and Albert Museum, 2018, London, UK; City Screen, Loop Barcelona, 2018, Spain; Frankfurter Kunstverein, 2018, Frankfurt, Germany; Nature Morte, 2018, Delhi, India; ZKM, 2018-19, Karlsruhe Germany.
Zabludowicz Collection Invites: Dedicated to solo presentations by UK-based artists without UK commercial gallery representation.
*Neural networks are programming models which are biologically inspired and learn from observing data. GANs (Generative Adversarial Networks) are neural networks which learn to mimic through generation and refinement.Jake Elwes, CUSP, installation view, Zabludowicz Collection, 2019. Photo: Tim Bowditch.