This is stuff from my ITP Glitch class.
We were introduced to one-line code that could generate music, as we studied Demoscene, which, among other things, tries to compact whole videos into ridiculously few lines of code by using generative algorithms and mathematics. This can be said to create computationally minimal art. A few users began to dabble in making music in this way (read this and this).
Videos of the captured music plus the code that generated them:
Here’s what I came up with, entitled, “Invaders”, via a link to the site. Or, below, an MP3 w/ HTML5:
Your browser does not support the audio element.
The examples from the blogs are much richer, more refined, and more varied than mine is. Mine sounds great, but it’s simplistic, and sounds mathematically generated as opposed to crafted.
Here’s the visual representation of the formulae, from the site:
But hey, try your hand at making this music! The web site for it is super easy to use!
I might have overthought this part of the assignment. I liked Epler’s random number generator which counts the number of chewing gum stains on squares of sidewalk. But I couldn’t think of something in my daily life that’s actually random.
In NYC, not only is it a grid-like city full of regular systems (crosswalk signals, daily work day routines, structured lanes and processes), but that oppressiveness of systems (if you want to see it that way) is relentless against things which do not go with the flow. Side note: perhaps this makes it a reliable medium for different industries and cultures to interact with each other in a standardized way.
Anyway, I also had a problem with this task because computers do randomization better than nature does. Nature is full of systems as well. It can be highly regular and predictable, even if it has long seemed like chaos to us. Computers, however, can give you a reliable distribution of truly randomized numbers, if they are given enough input noise to counteract any regularity in computers’ signals.
So, why do this task if code can do it any which way you like?
That said, I talked with my girlfriend and we came up with something suitable: counting the number of fallen leaves per hour in a day. While wind and time of year may affect day-to-day numbers, within the hour or smaller segments the variance is large enough to come up with reasonable frequent and random data.
It surprised me how regular any “random” data is. You could come up with any predictive range for many “random” numbers, such as counting people carrying coffee cups, women in skirts or jeans, number of people entering a store (which, I learned recently, big department stores have very accurate software motion-tracking to calculate for them).
We live in a world of systems which drastically affects our lives. We’re used to it, of course, but it reminds me of a book we had to read for my globalization class at Georgetown, which talked about the Meiji Restoration in Japan, putting Japan onto the western calendar and causing massive cultural upheaval to a culture which did not rely on regularized numerical calendar dates.