nonlinear dynamic system aka “chaotic good”, 2020

“The world is nonlinear. This fact has a profound effect on the behaviour of most dynamical and evolutionary systems: their future behavior cannot be predicted in the long run. The startling point is that even very simple classical systems are afflicted and not just such complex ones as the evolution of mankind or the weather.” (Lauterborn, 1990)
Chaos has been already studied and discovered in a wide range of natural phenomena such as the weather, population cycles of animals, the structure of coastlines and trees and leaves, bubble-fields and the dripping of water, biological systems such as rates of heartbeat, and also acoustical systems such as that of woodwind multiphonics.

These influences, furthermore, are starting to have an effect on music composition, particularly computer-generated composition in the last ten years or so. Discoveries of math and science usually have an effect on art and music: for example, although “we cannot say that the music of J.S. Bach is great because it is the aural equivalent of Cartesian geometry… we can hardly deny that it arises from the same Zeitgeist or whatever one chooses to call the nexus of intellectual, cultural and aesthetic currents that influence an artists” (Truax, 1990). So, too, “new music models will undoubtedly arise from the intellectual milieu that includes fractal geometry and chaotic non-linear systems” (Truax, 1990).

If we’re talking about music, one of the things that intrigues me the most is generative music. I was researching different ways to generate sound, when I stumbled upon an article about Markov chains and dug a bit deeper. As a result of my generative sound studies, I made a Max MSP patch, that generates new note and chord sequences from the MIDI files that are fed into it.Markov chains, named after Andrey Markov, are mathematical systems that hop from one “state” (a situation or set of values) to another. In probability theory, a Markov model is a stochastic model used to model randomly changing systems. Future states depend only on the current state and one or very few past ones.

This particular piece consists of Debussy’s “Clair de Lune”, “Africa” by Toto and my piece made in Ableton.

The order in which you feed in the MIDI files does not play a big role in how the song is going to turn out, as the patch switches between the pitches and tempos of them, but an important thing to note is that you won’t get the same result twice – the first time it could turn out very fast paced and rushed and other times it can be flowing and quite convincingly human-made. This mostly depends on which notes or chords are played first, as the Markov chain learns from and depends on the last few steps.

My initial idea was to execute this further in Ableton by making it harder to tell that this was generated by a computer, but after trying that out, I dropped the idea as it took away the chaotic magic of the pieces. In a time like this, when everyday tasks are being slowly taken over by machines and programs, the most beautiful thing we can do is to either embrace the new ways of life or turn away from them instead of trying to mask it with fake humanity. One could argue that these pieces have no structure and lack musical quality, which in and of itself is true, but that is the whole point.