Working with AI art sometimes feels like gazing into a pond of water. In a still pond, we see a clear, gently blurred version of ourselves staring back at us, while turbulent waters return rippled echoes of our shape. These changing reflections of ourselves are similar to images generated from data, which can be hyperrealistic depictions of the original, or images that are surreal and barely recognizable, as errors creep in. This exhibition looks at the way artists represent nature and humans, using the latest machine learning technologies to conjure seascapes, imaginary marine creatures, autumn leaves, and musings on the human form. Masks and faces akin to the grotesque rear their heads, reminding us of the early errors of these technologies and the eternal human fascination with depicting ourselves. These artists present AI as a tool to craft new reflections on perennial subjects, as well as a creative partner, conjuring new landscapes, creatures, and forms. Luba Elliott

Feral File  Reflections in the Water

Vadim Epstein&rsquo;s &ldquo;Pixie&rdquo; is a piece from an ongoing series using art imagery to explore the emergence of complexity. The neural network in this piece has been used here recurrently, reprocessing its own output without any additional inputs, as if jammed between broken mirrors. The models have been trained on a dataset that encompasses various figurative imagery &mdash; from photography to rough drawings &mdash; to enrich and intensify the visual experience. Part of the training data was synthetic itself: some of the source datasets were generated, adding another layer of mediation and thus distancing it even further from the real. Eventually, we observe an ever-changing, shape-shifting, loosely-controlled abstract flux, which appears more lifelike on its own, rather than the flashing snapshots of stiff flesh, stuck in convolutions.