Transformations in the image render pipeline extend beyond artificial augmentations like “super-resolution” in devices such cellphones, which refers to the process of introducing additional patterns and details to the image that may not have a real-world origin.
The hyperimage may orginate from the real word, but is expanded by synthetic (computer generated) render layers that transform it into a dynamic, modular object. The hyperimage does away with the notion of a static image. Instead, the hyperimage is procedural construct, where some layers may even be rendered seperately; at clients end and remotely, fragmenting the image as a distributed, evolving, decentralized networked process consisting of assets that can be partially (re)rendered, on demand or progressively.
Moreover, synthetic images are increasingly rendered by machines for machines, particularly in the realm of computer vision.
Unlike traditional Visual Effects (VFX) and Computer-Generated Imagery (CGI), which enhance images for human perception, these synthetic images prioritize machine interpretation over human perception, blurring notions of fidelity, value, and legibility even further.
Computer vision and Generative Adversarial Networks (GANs) use synthesized datasets to train on. A process that redefines the traditional scope of capture (which used to be constrained by spectral, spatial, or temporal parameters) introducing synthetic datasets as a new parameter of scope.
This process of recursive synthesis ultimately leads to ‘limitless’ quantitative (but not qualitative) resolution:
synthetic resolution is optimized for efficiency and automation, but alienates the human viewer as it transforms visual information into constructs that no longer resemble a traditional image.
The hyperimage may orginate from the real word, but is expanded by synthetic (computer generated) render layers that transform it into a dynamic, modular object. The hyperimage does away with the notion of a static image. Instead, the hyperimage is procedural construct, where some layers may even be rendered seperately; at clients end and remotely, fragmenting the image as a distributed, evolving, decentralized networked process consisting of assets that can be partially (re)rendered, on demand or progressively.
Moreover, synthetic images are increasingly rendered by machines for machines, particularly in the realm of computer vision.
Unlike traditional Visual Effects (VFX) and Computer-Generated Imagery (CGI), which enhance images for human perception, these synthetic images prioritize machine interpretation over human perception, blurring notions of fidelity, value, and legibility even further.
Computer vision and Generative Adversarial Networks (GANs) use synthesized datasets to train on. A process that redefines the traditional scope of capture (which used to be constrained by spectral, spatial, or temporal parameters) introducing synthetic datasets as a new parameter of scope.
This process of recursive synthesis ultimately leads to ‘limitless’ quantitative (but not qualitative) resolution:
synthetic resolution is optimized for efficiency and automation, but alienates the human viewer as it transforms visual information into constructs that no longer resemble a traditional image.
Struck by the beam of darkness that comes from her own time*, the Angel floats through space,
with no sense of day or night,
no axis of rotation,
no North or South...
...Progress, once symbolized by the Hologram PenRose-Stairs to Nowhere, is now resolved in ruins, rendering a monumental cairn of nonsensical vectors. Which suggests that either the Angel’s dataset is flawed or her tools cannot resolve the information.
At a loss, the Angel reflects on the Spomenik glitch, symbolizing the collapse of past and progress. She approaches it cautiously, tracing the dynamic edges of its vectors, composed of thick layers of poor-resolution sediments.
One of its shredded sides reveals a viewport, offering a glimpse onto its repository of render objects.
Like a media archaeologist from the future, she attempts to carefully reconstruct the Shredded Hologram PenRose to Nowhere. But its synthetic data follows machine-defined standards, producing nothing but a blue haze of noise. Realizing that the cairn is a collection of procedural images for which she is neither the intended user nor a possible interlocutor, she loses all confidence in resolving the data herself.
Momentary panic sets in.
...If her tools cannot render this data, perhaps another framework might re/calibrate the glitch.
In a last-ditch effort, she scans frequencies she usually keeps on mute. When deep within a C-band frequency, she detects a faint echo: a CyCLOPS.cy corner reflector, part of a decentralized system that recalibrates data misaligned across time and space.
And just like that, she resolves its phase difference, and her perspective renders clearly...
While a myth is an algorithm that functions as a tool respective to a time and place,
recursively,
an algorithm too can become a myth, connected to and lost with its iterative update and procedural context.
It will be her job to document these stories of lost and impossible renders.
with no sense of day or night,
no axis of rotation,
no North or South...
...Progress, once symbolized by the Hologram PenRose-Stairs to Nowhere, is now resolved in ruins, rendering a monumental cairn of nonsensical vectors. Which suggests that either the Angel’s dataset is flawed or her tools cannot resolve the information.
At a loss, the Angel reflects on the Spomenik glitch, symbolizing the collapse of past and progress. She approaches it cautiously, tracing the dynamic edges of its vectors, composed of thick layers of poor-resolution sediments.
One of its shredded sides reveals a viewport, offering a glimpse onto its repository of render objects.
Like a media archaeologist from the future, she attempts to carefully reconstruct the Shredded Hologram PenRose to Nowhere. But its synthetic data follows machine-defined standards, producing nothing but a blue haze of noise. Realizing that the cairn is a collection of procedural images for which she is neither the intended user nor a possible interlocutor, she loses all confidence in resolving the data herself.
Momentary panic sets in.
...If her tools cannot render this data, perhaps another framework might re/calibrate the glitch.
In a last-ditch effort, she scans frequencies she usually keeps on mute. When deep within a C-band frequency, she detects a faint echo: a CyCLOPS.cy corner reflector, part of a decentralized system that recalibrates data misaligned across time and space.
And just like that, she resolves its phase difference, and her perspective renders clearly...
While a myth is an algorithm that functions as a tool respective to a time and place,
recursively,
an algorithm too can become a myth, connected to and lost with its iterative update and procedural context.
It will be her job to document these stories of lost and impossible renders.
<*href: Agamben, G. What is the Contemporary? 2009>
Spomenik 2017.
Giant cairn of glitch, a monument commemorating no specific moment or entity.
4x4 meters projection mapped wooden installation.
As installed and produced by Transfer Gallery New York, for Behind White Shadows, on the surface: DCT SYPHONING.
A Hologram PenRose-Stairs to Nowhere.
Giant cairn of glitch (REFRACTIONS, 2024, WIP)
Shredded Hologram PenRose to Nowhere(REFRACTIONS, 2024, WIP)
CyCLOPS Retina
(in collaboration with Kimchi and Chips, commissioned Install for Thin Air @The Beams, 2023)
////////////////////////////
Refractions (2023)
is research project done in the framework of my European Media Art Platform residency at NeMe, Limassol, Cyprus.
(in collaboration with Kimchi and Chips, commissioned Install for Thin Air @The Beams, 2023)
////////////////////////////
Refractions (2023)
is research project done in the framework of my European Media Art Platform residency at NeMe, Limassol, Cyprus.
.
ALEV 01 + ALEV 02 
AKMS01 + AKMS02 
SOUN01 + SOUN02
ASGA01 + ASGA02 
MATS02 + MATS01 -
TROU01 + TROU02 IN MILITARY ZONE