My original idea for this piece was to create a single mega-creature made out of a large quantity of identical “cells”, much in the way that mold grows, where each individual cell functions mostly independently of its neighbors but end up in large groups due to each new cell growing directly next to its “parent”. I followed this idea directly into my final piece, where I tried to describe a three dimensional “mold” through its two dimensional growth and the intensity of the mold at any given point. The relationship that the user has to my monster is one of a cultivator and artist. I tried to create the type of control that a landscaper would have over their trees – not complete control but still a high level of ability to shape the growth of their plant. One can create a mold that grows in only a few directions, one with many interweaving branches or a very dense and “tall” one. I believe that I was generally successful in what I set out to achieve, but an issue that I was not able to solve are the random very intense bits of mold that sometimes appear along the edge of the screen. I also wish that the mold grew in a more random/independent of mouse way.
The name of my mold is quadrata cellularum.
Mold - OpenProcessing — Mozilla Firefox 2022-02-20 22-32-17
My creature is called Sping. In coming up with the concept for the interaction with spings I imagined that of a chihuahua who hates its owner but still needs them in proximity for comfort. I wanted it to always be biting the mouse but also chasing it out of need for company. It is also dumb, like a chihuahua, and will not avoid its poop, so the user should try and clean the poop before it gets there.
This idea was not super developed. I have issues with the entire thing, but it is what I could manage given balancing my other classes. A way this could be improved simply is to expand my creature to be more than 3 rects to give more of an impression of a living thing. I also could change the poops to be more poop-looking. Everything overall would benefit from more time.
This is my curious but cautious bug, “Lord Scuttles the third of Celastria”. This little guy is very curious about the red dot you’re dragging across the screen, similar to a cat trying to catch a laser pointer. However, due to his parents overprotective nature while raising him as a prince, he is very fearful of anything unknown that comes towards him causing him to run away shaking. To us he may seem like a simple pet, but back in Celastria he is a big name in the royal family and has appeared in the people’s favourite prince magazine every year since his success in developing a truce between the their kingdom and the honey badgers that frequently torment them, establishing mutual protection and sharing of resources.
I really liked how my project turned out, a very simple idea but it has a lot of personality to it. I tried adding microphone inputs where the sound would increase the range at which Lord Scuttles stays away from the mouse, but no matter what I tried my browser never wanted to pick up an input from my mic. Originally, the bug would just move towards the mouse and run away from it if you came towards it, but I thought it didn’t have any emotions to it, so I added changing colour and shaking to make it seem like he was traumatised by the approach of your mouse. Overall, I’m a fan of Lord Scuttles the third of Celastria, I think he came out great.
Since a lot of my work is inspired by nature, I wanted to explore a generative landscape that focused on simulating cloud movement. I also wanted to emulate the look of a film camera using overlaid lines and black bars, and try to incorporate more graphic design influences. It’s made with Perlin noise and Bezier curves.
I’m satisfied with the final result artistically, I think in terms of computational complexity / cleanness of code it’s lacking. I feel that I was kind of just messing around with things without really understanding their concepts (i.e w/ the Bezier curves) so I felt that it took me much longer than it should have to arrive at the final outcome. I changed the landscape from my first draft, which was originally going to generate “puffy” looking clouds with a blue sky, as I felt it was too similar to my clock piece.
I thought her series on artificial natural history was interesting because they still read very much like nature illustrations as a whole despite many of the details being unrealistic.
This is nuts. The best-generated tree I have seen in my lifetime. It is strange that I can’t find a single root in the image (use of transparency?) and the coloring algorithm is very effective.
Interestingly, I would argue that Effective Complexity is fully determined by human perception.
Mathematical Equations, to some people, are mostly chaos since the change of numbers in the equation would not invoke psychological change to them because they are not interested in extracting information from a blackboard of non-sense. To them, the image above reflects low effective complexity. To mathematicians, however, each bit of information is important and thus the image above reflects high effective complexity.
My Personal Note
“Generative Art Theory” talks about generative art as repeating execution of rule-based art, which incorporates many ancient generative arts not executed by computers.
“Generative Art Theory” by Philip Galanter discussed Effective Complexity. The intuition lies within although the trajectory of individual gas molecules is not predictable, the overall effect of gas property is well known only with little random error. But this is just an intuition, is there a way to find a mathematical definition for Effective Complexity? If we can systematically quantify such metrics, the next generation GAN could be optimized to achieve high Effective Complexity! (Given that the metrics is computable and well defined, we can have genetic algorithm do the generation. It doesn’t have to be differentiable)
The information theory counts every detail in the system as bits of information, but the human perception clearly does not.
Is the Effective Complexity only exist given human perception or is it more fundamental?
One way to model a complex system is to use statistical tools like discerning the mean and standard deviation. Two gas systems with different information will still have similar mean and standard deviation which aligns with human perception.
The article suggest that extremely low or high information complexity gives low effective complexityReaction-Diffusion System: simulation of chemical reactions that produce its own catalysts with changing diffusion rate
QUESTION 1B
My opinion about The Problem of Authorship: by defining generative art as repeating execution of rule-based art, all information is, therefore, encodable and can be represented by the rules themselves. If the final products follow exactly as the rules describe, then the final product, as a reflection of the rule, does not add additional meaning to the work. In this case, the authorship should fully belong to who wrote the rules. However, in the case of random number generation (especially for pseudo-random numbers), decisions (on which random number to use) are made by the computer, not the artist. Say, you wrote a program that uses total randomness to generate 100px by 100px images. Most of the time the resulting image is an image of white noise. However, it is still possible for the computer to generate something meaningful by small chance. This problem is magnified with artwork that involves latent space (typically in GANs) as this probability becomes larger. A computer can discover interesting random input to the latent space to “discover” an interesting artwork. At this point, we should attribute some authorship to that computer in choosing the right input. The “amount” of authorship we attribute to the executor should be proportional to the search space. This link to computational complexity is intuitive: as search space shrinks, the rule becomes more restrictive, and therefore more percentage of authorship should be rewarded to the rule-writer instead of the executor. In summary, for computer-generated art with uncertainties, I think the authorship should be split to both the rule-writer and the executor based on how restrictive the rule is.
I find this work of Sofia’s to be fascinating. It feels as if you’re looking at an old image, but what you’re actually looking at is fairly obscure. It’s a sort of uncanny plant life. It’s almost as if you’re looking at a historical image from a different world/universe.
I wanted to do something really simple for this project. I was getting too caught up with all the different extravagant ways I could approach this assignment, so I decided I would not do anything high tech at all. I basically messed up a double for loop and noticed that it looked a bit like a hand-drawn hill/horizon line. I think I have been wanting more and more to do something that looks like it comes from my hand, and this felt closer to having a material quality.
I started with these, and I’m not sure which I like better at the moment. Overall, I think I like this work. It’s extremely simple, code-wise and visually, but it felt like a return to letting go with my art and not really thinking too hard about it.
I am very interested in creating photorealistic quality using non-PBR tools. A map is relatively achievable and when those hand strokes are simulated by the machine, the quality increases but the authenticity still somehow remain as if it was crafted by hand. The entire image is made of many layers of clipping, many canvases, many Perlin noises, and many high school geometry. However, I strongly encourage the audience to not pay attention to the map that is drawn on the parchment because the map is clearly unfinished and badly made.
The most artistically challenging part is to make the parchment look real with a nice texture. The most technically difficult part is to figure out how clipping can work on pixel arrays. Of course, the project is over-scoped as I normally do. But since I think I can learn the most out of an over-scoped project, I will keep doing it until the time gradually shrink as I get increasingly familiar with 2D canvas coding.
