What I know about music is limited. It mostly consists of songs I’ve heard, beat drops i noticed were off tone or changes that did not make sense sometimes. I notice when the music is well composed but gets boring missing the change, or when i listen to music meaning for it to fade into the noise around me. It is really interesting looking at music from an information theory standpoint. Especially that I know about color theory. I know how complicated color mixing can get, I know the science behind it even when I don’t understand it, I know that you need to see art and understand it, even if you don’t know the science, to be able to create your own. I could not help but compare the two. One is music, the other is color.
Laurie Spiegel talks about music like my art teacher talked about color. The colors that fade, relaxing in the background like the low tones that blend with the noise. The change in music like contrasting colors in a painting bringing the boring but beautiful to an alive and attractive. The idea that one could change the tone not consciously knowing what they are doing, but subconsciously they are using memory, and information they gather from listening to compose a new piece. For me, its the same as drawing a new abstract piece without knowing why the blue looks good on a yellow background.
Drawing from randomness. whether a painting or a music composition, they may all seem random at times. as Spiegel said, “I consider randomness a relativistic phenomenon” something that seems random could make sense in ways we don’t understand. that is where information theory comes in. That is where we can say that the random composition we just made sounds good, and math can prove it. However I still wonder, if knowing too much about the theory of how something works, would that hold us back or move us further.
The way the authors talk about live coding as – they don’t explicitly say that – a way of breaking free from algorithmic routines resonates with me more than I thought it would. Something about coding is you always write a program to get it to do the output we expect. We always want it to reach the “perfect” point where it exactly does what we tell it to do; even with AI, we train models to do what we want to a limit we are scared of not being able to estimate the output results. with live coding, “When we write code live, we adapt it to our needs, and it adapts us in return.” they said everything is an average software engineer’s natural fear. “Then we do not use computers; they use us” as they also said, what every coder naturally fears.
I do love coding, programming, trying to get the program to work, trying to reach a specific goal. Hence the idea of letting the code, the output lead your process scares me. It is scary to not be able to expect the output. It is scary to write words not knowing what they will do. To combine lines not knowing what the perfect next line looks like. But in a way, it feels relieving. It is relieving the pressure of perfection, and diving into the beauty of an uncertain result. It will take effort to break free from the routine. “Turning the laptop into a kind of universal instrument whose own capabilities and boundaries can in turn be redefined.” is a sentence that any computer scientist with a goal will not understand.
I do love coding, programming, trying to get the program to work, trying to reach a specific goal. Hence the idea of letting the code, the output lead your process scares me. It is scary to not be able to expect the output. It is scary to write words not knowing what they will do. To combine lines not knowing what the perfect next line looks like. But in a way, it feels relieving. It is relieving the pressure of perfection, and diving into the beauty of an uncertain result. It will take effort to break free from the routine. “Turning the laptop into a kind of universal instrument whose own capabilities and boundaries can in turn be redefined.” is a sentence that any computer scientist with a goal will not understand.