Installation View, LEAP Berlin
Projection
Actors and Projection
Installation View, LEAP Berlin
Actors and Mirror
Electronics + Display of magnetic field
Fluxgate Magnetometer
Projection
Mirror
View from the back
Installation view, LEAP Berlin
Sideview
schematic / setup
data samples
Video
Installation View, LEAP Berlin
Projection
Actors and Projection
Installation View, LEAP Berlin
Actors and Mirror
Electronics + Display of magnetic field
Fluxgate Magnetometer
Projection
Mirror
View from the back
Installation view, LEAP Berlin
Sideview
schematic / setup
data samples

Mirage


Installation, 2014

"When one understands the causes, all vanished images can easily be found again in the brain through the impression of the cause. This is the true art of memory" — Cogitationes privatae, Rene Descartes

Mirage is a projection apparatus that makes uses of principles from optics and artificial neural network research. Mirage generates a synthesised landscape based on its perception through a fluxgate magnetometer (Förster Sonde). It registers the magnetic field of the earth, which is dependent on the earth geodynamo and its interactions with the activity of the sun, and feeds it into a unsupervised learning algorithm for analyzation. At the same time the algorithm, that is inspired by the principle of a Helmholz Machine, "dreams" variations of the previously analyzed signal.

This variations are translated into a two dimensional matrix that physically transforms a thin mirror sheet by 48 muscle wire actors. The surface of the mirror sheet changes analog to the systems state. A thin laser line is directed on the mirror surface in a acute angle to generate a depth landscape like projection on the wall. Through the constant shifting signals the projection resembles a subliminal wandering through a landscape.

In 2013 Geoff Hinton, one of the leading researchers in the area of artificial neural networks and deep learning, joined Google to support them on various products that use AI and learning algorithms. He introduced back-propagation algorithms for training multi-layerd neural networks. One of his contributions to the field of unsupervised learning algorithms is the so called "Helmholtz Machine", a machine that uses the principle of a wake-sleep-algorithm to consolidate its neural network. The alogrithm is trained during the wake phase by its sensory input. In the sleep-phase it cuts-off its sensory input and feeds the network backwards with random patterns. On its input layer (retina) it generates versions of is previously perceived images of the world.

I am speculating that the computers in the enormous Google data-centers cut off their perception (search queries, user behaviour, speech regognition, image data) once a day and start to "sleep". What do their “dreams” look like?

Article about Mirage by Mitchell Withelaw (Postmatter)

Produced with support of LEAP Gallery, Berlin