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Glow Box – A Window into an Artificial Mind

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Glow Box, a project by Yeseul Song & Michael Simpson, is a 3D printed hybrid object which imbues life into the object by displaying a real-time visualization of a neural network as it works to solve problems. The installation exploits the organic-like nature of the neural network algorithm and combines this with the almost magical ability of the physical object to appear illuminated without apparent electricity. The result is something which blurs the distinction between real and virtual imploring the viewer to question this distinction altogether.

Glow Box – Inspired by Nature

Nature has inspired mankind as longack as history is recorded. Among other things, our tools, techniques, and even aesthetics derive so much of their form and function from the clever decisions arrived at through centuries of evolution.

In more recent years, Nature has become a direct source of strategy for designers and researchers tackling some of the world’s most challenging problems. The neural network, a core component in deep learning, is no exception to this grand tradition. In their simplest form, a neural network models the high-level behavior of neural perceptrons. Essentially, they implement the basic functioning of a living brain. This technique has become invaluable in resolving problems that were once extreme challenges to quantify and compute.

Evoking Curiosity and Questioning Hybrids

But, categorically, what is a neural network? What do they look like? Do they think like we do? The ubiquity of these AI techniques begs for a more critical and creative understanding of the algorithms themselves. This project strives to do so by presenting viewers with a real-time window into the mind of a neural network as it repeatedly attempts to prove a simple equation. In particular, Glow Box evokes curiosity and, potentially, a questioning of the role for analog-digital hybrids as they inch closer and closer toward invalidating accepted definitions of sentience and free will.

In particular, Glow Box evokes curiosity and, potentially, a questioning of the role for analog-digital hybrids as they inch closer and closer toward invalidating accepted definitions of sentience and free will.

Glow Box is a 3D printed hybrid object which imbues life into the object by displaying a real-time visualization of a neural network as it works to solve problems.

The installation exploits the organic-like nature of the neural network algorithm and combines this with the almost magical ability of the physical object to appear illuminated without apparent electricity. The result is something which blurs the distinction between real and virtual imploring the viewer to question this distinction altogether.

3D Printed Glow Box – The Making Of

The cube itself was algorithmically designed and then fabricated using Stratasys Polyjet 3D printer. The cube has dimensions of 6” x 6” x 6” and is printed in optically clear material (Vero Clear) which exposes the object’s internal structure. On the contrary to optically clear print resins, that may result in printed optics or other geometrical shapes with a fully transparent internal core and a smooth surface finish, the higher haze values of the Vero Clear materials are utilized to absorb the emitted light.

Inside the walls of the object, a matrix of conduits curve to connect the cube’s bottom surface to the front-looking face of the object. These conduits hold thousands of strands of optical fiber which redirect light from beneath to be emitted from the front. This allows the analog object to serve as a sort of display when an image or animation is projected onto the cube’s bottom.

Images/videos from the preliminary 3D Printing research by the artist are found here

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