Image Alchemy and The out of Sight Nascency

By Oliver Hockenhull

What is a mark? An impression? A record? A signature? 

A definition — a discernible scar1 enlightening the face of the unknown, the canvas, the unrecognizable, the translucent and invisible container— that which is without a mark. 

A mark is a representation of something or another, something that is available for discernment. The foreground that is allowed for by the background.

We see what we are capable of seeing and some things which are there, right in front of us, we simply cannot see. There is a collection of there that for us are absences. Our brains are imperfect lenses from which we see what we can. 

We are burdened and relieved by the assumptions and predictions that our brains make to construct our perceptions.

A most recent optical illusions of motion-induced blindness show that our brains are blinded by information that it can’t reconcile. 

EXAMPLE 

First, look at any yellow dot as the figure moves. The yellow dot remains present and stationary. If you concentrate on all three yellow dots, they remain there as well.

But now concentrate on the central green dot. You will see one or more of the yellow dots disappearing and then reappearing sporadically. They are not disappearing —this is an error in our visual system. The dots remain and your brain simply doesn’t register their presence from time to time.

The illusion, a form of motion-induced blindness, shows the brain ignoring or discarding information.

Who knows the profundity of our blindness?  What we cannot see.

Creation is already in operation, already a given, it is there in front of us and it is everywhere. It is the mark we live in like a fish in water.

The term bindu means point or dot. It is a Sanskrit word and it refers to the point from which creation radiates. It is the sacred symbol of the cosmos, the primordial seed of nothingness. It is the singularity from which unity is experienced and from which creation is initiated or rather remembered.

One of the glory of this conceptualization is the premise that each mark, each dot, no matter how apparently small or insignificant is a mirror of this original point. 

Generative art, like all art demonstrates that the underlying processes of the creative endeavour, the creation of a something is the experience of the viewer and is determined by the viewer, even if that viewer is the creator. Yes it is in the pointed eye of the beholder — so conditioned by evolution and society —that beauty is defined, that is if it can be seen at all.

Generative art is a means to make the artist less a creator and more a composer. More a seer who relies on an intuitive approach to a palette of compositional material than a doer marching out to create what is an individuated remarkable marking. Generative art functions as the role of editorial observation angling a stack of quotation and the selection of results from a massive stack of possibles. 

Maybe the rise of generative art has come to our particular age not only because our tools allow for such encyclopedic and extraordinarily potent analytical and compositional creations but because we are the ancients. 

We are the heirs of a history of creative visuals, the entire recorded history of the human species, a cumulative process of art making, paintings and representation, abstractions and visualizations.

Photography which steals the forms of the world and gives us a document of the theft could be considered the first generative art. The pencil of nature, by the simplest of interventions, the click of a shutter, generates an image of what is placed in front of it — no author or artist necessary. The image is infinitely reproducible and can be conditioned to    conform to different presentation platforms.

Generative artists design systems or use the tools of such systems using language rules, machines, algorithms, GAN systems, l-systems, chance and/or genetic sequences or evolutionary builds to generate a product that serves as the work of art. These systems can be digital, biological, chemical, geometrical, mathematical, or manual, and are practiced in a variety of disciplines, including architecture, poetry, literature, animation, and visual art.

In this phase of a stream of my own work it is a breeding of multiples, variations, and recombinations that delight my mind’s eye with their difference. 

I have recently been working on various A.I. art platforms generating thousands upon thousands of iterations, stylistic variations that are interpretive results of the machine of collected and catalogued imagery originally imaged by myself or found within the public domain. 

The most fascinating, even awe inspiring aspect of this process is seeing  the result of a learning curve. A curve that is the bias, the favours of one’s own mind revealed by the extraordinary determination and productivity of the electronic brain. A learning in process of what constitutes the folder of images that are used to learn from, to create the new in the style of the seeing of learning.

 

The trial and error and trial and error correction of machine learning is a particular stream of generative art. GAN stands for a system that uses generative adversarial networks to uncover the new in the old. It is a technology of analysis and creation that uses a dialectic process to train a model. Generative modeling is an unsupervised learning task in machine learning in which the laws or patterns in input data are discovered and learned so that the model can be used to generate or output new examples that could plausibly have been drawn from the original data set.

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“These mistakes are my teacher. No books, no sensei. Having come through to this point, I have a profound faith in the process. Coming at it from zero knowledge. Really one goes around the zero, not one, two, three, twenty, one hundred. Staying right at the “not sure” place gets one to the attitude of: “I don’t really know all about this, but I’m going to give it a try.” And suddenly it happens. Learning.

From Suzuki Roshi little book on zazen comes the saying “joshaku shushaku:” mistake upon mistake compounded upon itself. It is a compounding of all your mistakes that is the sum total what you know. You never leave the zero. You never leave the whole.”

See: https://www.shakuhachi.com/KJ-Interview.html

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The proposition is that the beginner’s mind as understood in Zen is that which is unambiguously in the moment. The individual too is  indistinguishable from the moment. This is an attunement with the fantastical blotch, the mark, that is the is of creation.

The artist role here is one of imagery alchemy, colour, texture and perspective, combinatorial, details in the artistry of curation.

The generative morphic process of GAN modelling for visual art builds, if sufficient time is given over to the modelling and there is sufficient but not too much variety in the modelling folder results in serendipitous images that are strikingly unique. The calculations of the common and the specific, salient features of each image as it relates to each other image in the morphing source folder is more data than what a normal human can work through in years if not life times. 

Generative adversarial networks are based on a game theoretic scenario in which the generator network must compete against an adversary. The generator network directly produces samples. Its adversary, the discriminator network, attempts to distinguish between samples drawn from the training data and samples drawn from the generator.2

What may results from this process is the creation of images that contain aspects of the original images that are so reinterpreted that novel aspects, unseen aspects of the original images are discovered or revealed.  One can experience the production of new original art productions, images that were previously unseen but exist in a nascent, invisible potent form within the failings and simplicities of our own perceptions.

1  “What is needed is my wound against your wound.”  George Bataille

2 Deep Learning (Adaptive Computation and Machine Learning series) Illustrated Edition by Ian Goodfellow  (Author), Yoshua Bengio  (Author), Aaron Courville, Page 699

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