Work

lubar – LookingOutwards02

Procedural Lake Village by Anastasia Opara, 2016

This is an image featuring a series of lake houses that have been generated by a procedure "all the way from silhouette to final texturing*"

Seeing this blew my mind, in retrospect it makes sense that in movies and video games objects would have some generative component to their creation, but I had really never considered this to be something that could be done with so much, I suppose, artistry.

These generated houses have such a beautiful, whimsical, and hand touched and imagined form, texture, and feel. Realizing that this kind of world building can take place in a generative programmed structure is eye opening. The algorithm itself likely works as a generative 3D model with specific constraints and elements such as window, door, walls, roof etc that are matched with specific types of (also generated) textures. This all balances the order and disorder beautifully. The creators artistic sensibly comes through in the style of the houses/the constraints and textures and the natural forms that this algorithm follows.

Link to work

 

iSob-LookingOutwards02

For this post, I'll be discussing Daniel Brown's Dantilon: The Brutal Deluxe (2016.) The title might refer to the Brutalist architectural style of the rendered fractalline buildings. Though I don't know anything about architecture, I am interested in dream landscapes both neurobiological and artificially generated. In the waking brain, hippocampal place cells fire in response to a specific known location and orientation. More mysteriously, they also fire during sleep, when the body itself is still, but new and old memories flit through the hippocampus on their way to longer term storage. That specific place cells exist calls into question the sense one typically has of knowing unquestionably where one is located. To me, computer-generated landscapes take on the sense of dreamlikeness when they inspire a sense of familiarity, like a dredged-up memory, while simultaneously inducing discomfort and displacement.

The imagery here appears to have been created with a three-dimensional fractal (probably a recursive function drawing any of a selection of features at a given level, from the blocky planes that make up the 'walls' of the buildings down to their individual window detailing.) The work has a fairly high effective complexity, as every instance (at least that the artist included in the album) is perceptually unique. It does, however, skew more towards order than chaos. The rules of the generator are strict enough that all the architecture seems physically possible and remains photorealistic, albeit somewhat gravity-defying.

tli-LookingOutwards02

Happy Place by Jared Tarbell

Happy Place is a Processing piece formed by placing nodes along the perimeter of a circle and instructing them to move towards "friends" and away from non-friends. I can see from the source code linked in the web page that it is a fairly simple program wherein at each frame, each node moves then adjusts its position to find a "happy place" between moving towards friends and away from non-friends. All functions and objects are named accordingly, with nodes being called "Friends" and their movement adjustment function called "findHappyPlace".

Happy Place calls out to me because it evokes memories of working physically with charcoal despite being computer generated. It looks like a drawing formed by shaking a piece of paper with charcoal dust on it, which may very well be a physical analogue to this work. Happy Place is a textbook example of effectively complex because it demonstrates chaos created by a combination of randomization and simple rules. The "initial condition" is determined by random placements, but the resulting movement is dictated by clear rules. As Galanter suggests, this leads to chaotic dynamics even though the systems themselves are deterministic, and we see evidence of the butterfly effect and sensitivity to initial conditions in the images that Tarbell displays. Tarbell himself includes varying simulation results, such as when the group of friends migrate away from the circle entirely, or when two friend groups repel each other to opposite sides of the canvas.

tli-Reading02

Question 1A.

I think games with very simple rules that are played by humans are a good example of effective complexity because they are great stages for emergent interactions. Games that come to mind are the loop activity we did in class and r/place, where a rule as simple as "You can color a pixel every 20 minutes" allows for complex social interactions. I choose these as examples because they are a combination of order (simple rules) and disorder (human individuality) that constitute a complex system. Perhaps the only point of contention is whether these examples are truly generative, because the artist(s) are not removed from the decision-making in the way that Galanter emphasizes in the beginning of the text.

Question 1B.

I relate the most to the problem of meaning because I find it something that I struggle with in all forms of art. Galanter highlights generative art's inclusiveness of all forms of "meaning", whether it be presenting the system itself, invoking awe, or delivering social commentary. Because of this, I find it hard in general to evaluate the critical value of my ideas. At the same time, I find it liberating to not have to evaluate the critical value of my ideas because all delivered meanings are valid within the realm of generative art, including the lack of "higher" meaning beyond being interesting. Galanter also mentions a radically bottom-up "truth-to-process" approach, which I find intriguing but also personally difficult to practice. As an artist, I enjoy adopting a director position over my projects, which makes it difficult for me to relinquish control to the system.

sansal-LookingOutwards02

Drawing Water is an art piece which uses water usage and accumulation data to create a piece illustrating the disparities between where water is collected and where it is actually used. What I admire about the project is that it is almost a passive-aggressive political swipe to reveal hidden truths of the environmental sector, because it shows that the creator is willing to speak out against the government through his art and is not afraid of what repercussions that may cause. I believe the algorithm used charted out where water was collected versus where it was used, and plotted it on a specialized graph with different shades of blue meaning either different collection methods or different types of water. The piece shows that the author does not use very complicated algorithms to accomplish his work, but uses them in a creative way to make it easy to read and understand. The work's effective complexity is in its data collection, and the artist has balanced order and disorder by presenting that data in an aesthetic yet revealing way to expose the hidden truth. At first glance, the numerous water paths on the artwork seem over the top and convoluted, but after some time it becomes easier to see which areas of the country use more water compared to which areas produce the most water. 

 

David Wicks, Drawing Water, 2011. 

http://sansumbrella.com/works/2011/drawing-water/

sansal-Reading02

1A. Going back to teamLab once again, I believe their piece BORDERLESS exhibits a high effective complexity. The experience of the art itself is completely different for every viewer, as the programs and displays are almost completely interactive, depending almost entirely on user input and movement. It sits in the middle of total order and total randomness, because the art generated is created by the same algorithm (total order), but the art's conveyance and comprehension is different for everyone (total randomness). 

 

1B. Problem of Authorship:

I took the mini-course Art & Arduino last year, where I thought about this specific idea for a long time, because my final project dealt with a robot producing art based off of human input. Especially since I am a digital artist interested in computer graphics and animation, this problem is very close to the career I want to pursue. I came to believe that yes, since the artist is the one creating the program and coding the processes that the system uses to generate the art, the authorship of the artwork can be credited to the artist and not the machine. If the artist is simply using specific programs of the machine and changing the input values to vary results, then by the transitive property, the artist is effectively creating the artwork itself as well.

MoMar – Reading02

Cities that have been around since the middle ages are prime examples of effective complexity. In the olden days, urban planning was not widely used so people typically built buildings where they wanted to. On the scale between total randomness and total order, it's around the middle because as time progresses, the city gets more organized. There is a clear division between the two with the wide road surrounding the old city.

 


Zapra – Interruptions

View code

Observations / Assumptions:
  1. The image is a white square with black lines
  2. There are many short lines of the same size
  3. There are seemingly random gaps in the lines
  4. The lines form a matrix of rows and columns
  5. The lines are centered around a midpoint of equal distances apart
  6. Most lines are angled left or right, but have a slight proclivity towards the vertical
  7. There are often several gaps in the image of different sizes
  8. Some gaps extend or go over the edge of the grid
  9. There are about 60 lines in each row
  10. The space between each row is less than the length of the lines (if all lines were vertical, they would overlap about halfway)
Reflection

Some of frustration I ran into with this project was based off an incorrect assumption I made about how the lines were drawn. I had assumed all the lines were spaced equally based on the top endpoint rather than middle. Once I realized this, I struggled to find an effective way to center all the points around these midpoints (but once I did, I audibly yelled "YES!" alone in my apartment and gave myself a high five). I haven't done much in-depth coding since last year, so as I've progressed with this assignment I'm starting to remember more and more. I think ideally I could still tidy up my code, but I at least feel satisfied with the end result.

Some previous versions:

iSob-Reading02

1a. An Example of Effective Complexity

The human brain is biased towards total order: many rules governing brain organization lead to strong similarity between brains. These rules govern how neurons will be constructed, and how they will be linked together in patterns of excitation and inhibition that ultimately give rise to predictable output, e.g. the same(-ish) perception given a constant stimulus. But a brain with too much order could accomplish no more than an 80's-era AI expert system. The formation of unique memories in a newly-formed, 'blank slate' brain (which leads to learning) could be seen as an expression of chaos within the orderly system.

1b. The Problem of Meaning

Can and should generative art be about more than generative systems?

This problem is particularly conflicting to me because I'm interested in the mistakes that come out of a generative process. I like things that didn't come out as intended, like a GAN-bred puppy with three eyes. In that way I am interested in generation itself, how mutations are introduced, and how society turns against these unfortunate 'failed' instances of an algorithm. But, unlike the 'purity' of the process  Galanter describes, where the artist has no particular goal in mind, I am always obsessing over making exactly what I wanted to make. Ideally, I would want generative art that I make to reach a point between the purely generative sublime and the dirty, ordinary world of meanings and signs.

lubar – Interruptions

Observations:

  1. The artwork is a square
  2. The centers of each line segment are in a grid form
  3. The line segments appear randomly rotated
  4. The line segments occasionally intercept
  5. There appear to be 57 possible lines across each axis
  6. The piece has a blank margin
  7. There are clusters of blank spaces that appear in random locations
  8. The clusters of black spaces are not uniform in size or shape
  9. The length of each line is slightly less the double the distance between each line
  10. The lines are thin and short

Interruptions Sketch Link

In the process of creating this, I found the rotation of the line segments to be particularly frustrating, although I initially assumes that that would pose the least challenges. The method that I was using involved the rotate() and translate() functions and it took me a while to figure out to use multiple translations I needed push() and pop(). Overall however, especially after discussing Perlin noise a bit with Sophia, I found the other elements to run smoothly, although not perfectly when compared with the original pieces. Molnar's original interruptions have a slightly 'free-er' quality that I was not able to capture despite playing around with it for a long time. Despite the slightly denser interruptions, I am content with how the reproduction turned out, and I would be curious to know how that effect was/might have been achieved without Perlin noise, as I haven't quite been able to wrap my head around it yet.