Raul Altosaar ~ 2020.11.18
Music 256A, Stanford University, Fall 2020

Lost

Lost is an audiovisual narrative experienced from the perspective of a neural network. Having escaped out of an abandoned, self-driving Mercedes, the neural network/user finds themself in a devastated world. Humans have disappeared. Life is gone. The neural network is lost.

As they explore their surroundings and interact with their environment, voices, pulses, and waves of sound begin emanating out of the objects they touch. The voices tell a fragmented story; of loss, anger, uncertainty, pain, and difficult decisions. The weight of these stories transfers to the neural network. As they touch each object, their body becomes heavier and heavier, until they are barely able to move. A visual progress bar lights up whenever they touch the objects, indicating their current heaviness.

As the neural network moves through the world, the source of the voices and stories becomes unclear. Are these human memories, left behind from another era? Or, are they the neural network's memories? Has the neural network's consciousness become completely embedded into their environment? Are they speaking through the objects? Designed to explore these questions, Lost probes the entanglement and transmutation of machinic and human trauma.

Instructions:

You may download and execute a build of Lost by clicking: here!