Abyss of Light

Abyss of Light is divided into three screens and into three acts, the traditional structure of classic narrative film. In the first act, all the images synchronize to form a single panorama of Bryce Canyon in Utah. In the second, the screens break away from one another into three parallel sequences wherein each projection shows the same one hundred images at different speeds. In the third, all three images synchronize once again to form a single wrapping panorama of Death Valley, California. The work is an ode to the American western, one of my favorite film genres. Despite my admiration, however, my desire is not to imitate westerns. Instead, I set up an abstraction in opposition to the idea of narrative, something that can be seen in all of my work. In Abyss of Light, continuous disruptions of the American landscape document my refusal to see the land as backdrop for man’s heroic conquering of the wild; instead I see it as a foreground, a subject to be contemplated for itself and for which wildness is a state of grace.

Abysmal
Abysmal means bottomless; resembling an abyss in depth; unfathomable. Perception is a procedure of acquiring, interpreting, selecting, and organizing sensory information. Perception presumes sensing. In people, perception is aided by sensory organs. In the area of AI, perception mechanism puts the data acquired by the sensors together in a meaningful manner. Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. Inspired by the brain, deep neural networks (DNN) are thought to learn abstract representations through their hierarchical architecture. The work mostly shows the ‘hidden’ transformations happening in a network: summing and multiplying things, adding some non-linearities, creating common basic structures, patterns inside data. It creates highly non-linear functions that map ‘un-knowledge’ to ‘knowledge’.