Generative Adversarial Nausea
(5 images. alt text included)
The images displayed on ten separate LCD panels are made by training a neural network to learn the visual attributes of two distinct sets of digital photographs. One set consists of hundreds of stock photo thumbnails of nauseated people, while the other is made up of a nearly equal amount of selfies I have taken over the past four years while living with an undetectable chronic nausea. Made while working at playform.io
Hiatal
Closer examination of the stock images used in my training process show humans trapped in exaggerated moments of pain while inhabiting highly spaces. There is no space for a mild nausea or mild investment in place. Hiatal subverts these images by re-animating amorphous figures within them who deflate, hollow-out and slip into the cracks; simultaneously occupying and undoing subjecthood and place. They expose their aspirational surroundings as equally malleable backdrops that can be unveiled, blown away, and thrown up.
Hiatal. 2020. 7 minutes, 50 seconds. Digital Video.
Image Description: This video is comprised of five separate scenes, each taking place in the environment of a stock photograph: a couch in a living room in an exposed brick apartment, a large bedroom with a full-sized mirror and bright light from the windows, a clean kitchen in a bright white apartment, a bathroom consisting of a single white toilet, and a long hospital hallway with a single vanishing point. There is one figure in each of the scenes, and using the 3D software Blender, I attempted to turn each of these figures inside out. In the process, they deflate, twist, hollow-out and slip into the cracks of their environment. The sound emanating from two speakers hung on either side of the video projection is used to further bring the scene to life. The rustling of fabric describes the movements of the figures on screen, while radios, birds, clocks, and other voices, all describe things happening in the periphery.
Excerpt, Hiatal. 2020. Documented at Mason Gross Galleries, New Jersey.
Image Description: The video described above documented in an exhibition space where it is projected to fill the entire width of a wall. A one minute segment.
special thanks to Ahmed Elgammal & Playform.io for project support.
Exhibitions:
- Devil in the Details. Mason Gross Gallery. Rutgers MFA Thesis Exhibition. New Brunswick, NJ