Mohammad-Ali Rahebi

 

Sensitivity to initial conditions is the death of reductionism. It says that any small uncertainty that may exist in the initial conditions will grow exponentially with time, and eventually (very soon, in most cases) it will become so large that we will lose all useful knowledge of the state of the system. Even if we know the state of the system very precisely now, we cannot predict the future trajectory forever. We can do it for a little while, but the error grows exponentially and we have to give up at some point. (Baranger, 2000)

Enter feedback and cybernetic cross-checking and self-correction.

Earlier in the essay quoted above, Baranger teaches us that classic, non-chaotic science relies on calculus, the invention of Leibniz, the tool that can map curves via obtaining a function y=f(x); a compression-function that tries to come up with a simplified formula for any curve drawn on a Cartesian diagram. It is the bet that even in the cases of the most complicated curves (as an aggregate of connected points in, e.g. two-dimensional space), there is a way to designate them that is simpler than (or, in a worst-case scenario, the same as) the data itself. Leibniz even has a compression-efficient god.

Now it is in no way an accident that Leibniz has blind monads and thus needs the perfectly predictable world of pre-established harmony (and argues for a compression god-algorithm of world-optimization). Now that we have seeing monad-machines, we see that curves and calculus are too reductive and representationally poor because representational in essence. With this comes greater computability of very complex situation: the model, if any is even necessary, changes from instant to instant by observing the system in real-time and self-correcting as necessary: backpropagation.

The god-function of Leibniz is what is supposed to create the most complex and plentiful world-plenum from the simplest possible plan of action, thus creating the best of all possible worlds through its efficiency, which is defined in terms of compressive power. The Cybernetic Organon is the death of the Leibnizian efficiency (which operates in the blind world of pre-established harmony, itself a theory of pre-feedback machines unable to see, though unbeknownst to Leibniz himself).

Are cybernetic machines classifiable as “living machines?” Does self-correction amount to self-organization? An unsupervised deep-learning algorithm operating on Big Data is an example. By processing and training with data, the machine (a machine can be a piece of software running on some hardware, dedicated or not) changes from a state of indeterminate “noise” (where all the node weights are assigned either an equivalent value (e.g. 0 or 1), or random values uniformly distributed) and organizes itself (i.e. its weights and biases, or even the function etc.) into a singular entity as unique as anything and at least as complex as the data it feeds on for its organization, i.e. it is at least as complex as its environment (which is given to it qua data, structured or not).

While the cybernetic machine is at least as complex as its environment/data, in Leibniz’s compressive organon the god-function of calculus is at most as complex as its environment.

The Cybernetic Organon operates in a world of windowed monads and constant feedback, real-time updates of the environment and as such can afford a higher order of efficiency which takes complexity into account and welcomes it into itself as a computational feature deployed through an intelligence without representation, an intelligence without transcendence.

Bibliography

 

Baranger, M. (2000). Chaos, complexity, and entropy. New England Complex Systems Institute.

Mohammad-Ali Rahebi

خَلَقَ الْإِنسَانَ مِنْ عَلَقٍ

(Made Man from Alaq (accretion/clot

 

The catatonic knight, the “passional” knight, stands in the field of snow staring at the red blood amidst the white expanse; he has forgotten where he is or who he is or why he came to be there. Only one subjectivity at a time; only a super-plastic, re-adjustable, “adaptive” set of behaviors in each given situation. Deleuze’s Perceval is a cybernetic machine: he is taken out of the quest-milieu and into that of romance, a catatonia waiting for further assignments of action-milieus. He is capable of forgetting, completely, even his own name, and what is much more important, even his low-level bodily habits, and so becomes the emptiest subject, container, de-calibrated even of former habits to allow for maximum potentiality of becoming: if you become nothing, you can become everything. This is why it is only Perceval, the “idiot” knight of recurring amnesia that can have a chance at finding (becoming?) the holy grail of Cybernetic Capitalism.

 

Pasolini’s Arabian Nights: characters so flat and contingent as to be completely unbelievable. They are purely affective feedback mechanisms. From crying and running urgently after the lost beloved, they happen into sexual encounters that has them immediately forget and re-calibrate their behavioral pattern and start laughing and making dirty jokes. Burning with the desire (nay, the appetite) to be finally united with the beloved, they suddenly fall asleep at a moment’s notice; even the viewer herself is thrown from one story into another without any delay.

 

But here one must tread carefully for the Knights and the Lovers in Arabian Nights are but fantastical limit players in the game of machinic immanence and where they tread, bodies can never go. Yes, we have spoken of the super-plasticity of the Deleuzian BwO-Shoggoth, Capitalism’s wet dream of what a consumer should be, and indeed a rheology of bodies and networks is needed because what the Cybernetic Organon produces goes beyond the plasticity of the organic and into the realm of the hydraulic, the fluid at their shear points. When you sing the song of “the body is the body” and renounce organs and organization in favor of a destructive plasticity, it is to the new, machinic god of network-Occasionalism that you pray, and “the Singularity” is the only solace he falsely provides for the death of our selves in the name of the body, a body that never was ours but the machine’s shadow on the wall.

clot2
Ebrahim Zargari-Marandi – Cyclope – 2016 (bw)

Where does the body meet the flows of the networks of data and desire? How does Cyber-Capitalism attempt to realize the connection of the (habituated) body and flat flows of its ever-expanding network (for Cyber-Capitalism is first and foremost, a connector)? Enter liquefaction. Or rather attempts at liquefaction; attempts at lowering the shear point of the habituated organic body, pushing it towards maximum “creativity”.

We began with the human as the accretion of habit over time, the production of human subjectivity from out the fluid flows of experience via the clotting that is “sensory gating” or, in more common terms, adaptation and habituation to stimuli. Thus the human subject has as its genesis the alaq, a clotting, a self-attaching that is its only “essence”. An accretion that is to be understood in terms of neurosis qua biologically-necessary habituation. Thus is the human made a Neurotic, a NARP. But it is in fact not so much a genesis than an epigenesis: the accretive organism that is the human being in its fleshy incarnation assimilates itself through a clotting and jellification, a habituation that draws in and accretes the stimuli in all their historical specificity and makes them its own while being in turn shaped by their force and form. A dialectic of the flesh, a flesh that does not forget. It is a flesh that we share with the non-human animals (Hegel already defined habit-based subjectivity as common to all animals).

In thinking of the human we should think not of what constitutes it vis-à-vis the animal, as has been done in the whole history of philosophy, but of what unites it with the animal or the organic vis-à-vis the artificial, the machinic: utter amnesia. While human amnesia does retain the minimum identity of the habituated subject (working memory, bodily habits like reassembling a gun or riding a bicycle), the AI bases its efficiency on its ability to forget its specialization, its training, and become generic once more, in order to be placed in another data-milieu.