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Deep Bore
2021 (engelsk)Kunstnerisk output (Ogranskad)
Resurstyp
Blandat innehåll
Fysisk beskrivning [en]

EMMA 2w laser, raised flooring, server box, PLA 3D printed GAN-generated objects, custom web browser and 4K application

Fritextbeskrivning [en]

Solo show at Cattle Depot Artist village in Hong Kong from October 02 - November 05 2021.

Abstract [en]

DEEP BORE revolves around a data center raised flooring formation that operates as a stage to view a live-generated, never-ending borehole projected onto the floor. The hole is perpetually digging through to a virtual environment that acts as a liminal space, or bridge, between the physical site of the gallery, its surrounding environment, and a realm of virtual and real-time content. This includes live browser updates to the Reddit homepage, GAN-generated objects and images from a GAN trained on tools and technologies throughout human history, and other items that materialise, float, and fall into the void on the screen.

The installation is interested in drawing a spontaneous environment that allows viewers to enter through interfaces that are site specific rather than the normal screen space we encounter on a daily basis. The visual material reflects the remnants of human technological production, prehistoric caves, and rare-earth mining tunnels. There is a direct reference to data mining, crypto mining, and data centers that have sprung up around the world. The installation creates a space of reflection on the intangible data-points, machine learning algorithms, clouds, and rendered objects we often encounter, touching on their real world presence and effect on the environment, consciousness, and culture.

sted, utgiver, år, sider
Hong Kong, 2021.
Kanal
No.8 Cattle Depot, Hong Kong
Emneord [en]
Artificial Intelligence, AI, Video Art
HSV kategori
Forskningsprogram
Konstnärlig forskning
Identifikatorer
URN: urn:nbn:se:umu:diva-234574OAI: oai:DiVA.org:umu-234574DiVA, id: diva2:1931037
Tilgjengelig fra: 2025-01-24 Laget: 2025-01-24 Sist oppdatert: 2025-02-21bibliografisk kontrollert

Open Access i DiVA

Photo of installation(2868 kB)0 nedlastinger
Filinformasjon
Fil IMAGE01.jpgFilstørrelse 2868 kBChecksum SHA-512
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Type imageMimetype image/jpeg

Andre lenker

Exhibition information

Person

Shanken, Daniel

Søk i DiVA

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Shanken, Daniel

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Totalt: 28 treff
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