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.

In An Information Theory Based Compositional Model, Laurie Spiegel initially explains information theory, a mathematical theory optimizing signals for communication in noisy channels and addressing communication degradation in such environments. The author illustrates a drawback of applying information theory, noting that prolonged exposure may lead to increased listener boredom, as people can predict each note before hearing it.

Subsequently, the author delves into the use of noise in music to enhance its functionality. Introducing unpredictability through noise amplifies uncertainty in each note’s resolution, rendering it more musically interesting. This form of random corruption, distinct from random generation, involves replacing explicitly defined information with random data at random times to counteract redundancy and increase entropy in music. The author asserts that “music is self-referential and sensory rather than symbolic,” and defines music as “an art of sound in time expressing ideas and emotions in significant forms through the elements of rhythm, melody, harmony, and color.”

The concept of randomness has provided creators with limitless possibilities, and an increasing number of music programming software applications are incorporating this randomization utilizing a more diverse set of noises to enable individuals to create music, even without a background in music theory. Although unlike the author’s idea of random, my idea of “random” is more along the lines of “one can make simple music with many kinds of clips that already exist”.

Laurie Spiegel’s article is a captivating exploration of the intersection between information theory and music composition. I appreciate how she breaks down the concept of entropy, using it as a lens to analyze the limitations of a simple melodic pattern and the power of introducing controlled noise.

It’s fascinating to consider how entropy, anticipation, and noise play crucial roles in shaping our musical experiences. This brought to mind the crafted buildup of climaxes, which, despite their intentional, predictable nature, manage to surprise us by deviating from the established pattern. It’s a delicate orchestration of tension and release, inviting nuanced anticipation. It contrasts with the randomness introduced by noise, aligning more with a controlled entropy.

I wonder if information theory has gained widespread use among composers working with computers, and if not, why that might be the case.

Laurie Spiegel’s exploration of “An Information Theory Based Compositional Model” presents a riveting intersection between the mathematical realm of information theory and the creative domain of music composition. This model, detailed in the Leonardo Music Journal, ingeniously applies concepts of signal optimization and noise management to craft musical compositions that challenge our traditional understanding of harmony and predictability.

Spiegel’s approach suggests that ‘noise’—often deemed undesirable in clear signal transmission—can be an essential element in creating a dynamic musical experience. This concept not only pushes the boundaries of compositional techniques but also prompts a deeper introspection on the nature of creativity and communication. It poses a compelling question: What defines ‘noise’ versus ‘signal’ in our perception, especially when these distinctions are inherently subjective?

Moreover, Spiegel’s contemplation on the essence of composition—whether it’s a genuine act of creation or a transformation of existing materials—invites us to reconsider the notion of originality in art. This perspective resonates with the postmodern view that creativity is a process of recombining and reinterpreting the ‘noise’ of our cultural and personal landscapes into coherent expressions. In essence, Spiegel’s model transcends its mathematical origins, offering a metaphor for the human condition. It reflects our own cognitive processes, where the ‘noise’ of competing memories and thoughts shapes our creative output and perception. Through this lens, Spiegel not only expands the possibilities of musical expression but also encourages us to find meaning and beauty amidst the chaos of our surroundings, harmonizing the dissonance of modern existence with the melody of human creativity.

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.

As a newcomer to live coding, I find the text to be a captivating journey into a realm that transcends the boundaries of conventional programming. Given my little experience with python, c++ and p5.js, the idea of writing code in real time, modifying programs on the fly, and projecting the entire coding process to an audience is both exciting and terrifying. The concept of making software “live” goes beyond my first impression of coding as a static process. The reciprocal relationship between the coder and the code, in which both adapt to one other in real time, provides a refreshing perspective. It challenges the idea of code as a static set of instructions by introducing a dynamic, changing entity that responds to the coder’s requirements.

The text’s analogy of live coding to an improvising composer in the context of music provides a relatable comparison. As a singer and songwriter myself,it’s like envisioning my computer as the instrument, much like my trusty guitar, and the lines of code as the chords forming the foundation for my digital melody. Embracing this paradigm allows me to approach live coding from a musician’s perspective. My laptop evolves into a diverse instrument, and the code serves as my musical language. Live coding creates a digital stage on which I can dynamically compose, improvise, and perform, transforming my code into a song that I may sing and share with the world. 

Thus, for someone new to live coding, this text provides an introduction to a dynamic and evolving field. It inspires me to explore coding’s creative possibilities, emphasizing improvisation, transparency, and the transformative power of live coding. It defies established beliefs about code’s rigidity, portraying it as a living, breathing entity that grows in real time, and invites me to embark on an intriguing journey that promises to be experimental and fun throughout.

This opening excerpt from Live Coding: A User’s Manual offers a compelling definition (or rather, a set of definitions) for the practice, art, and philosophy of “Live Coding.” I was immediately intrigued by how the author(s) addresses the strange nature of writing a book about live coding, much less one that seeks to be a manual (“there is something perverse in writing a book about live doing”). Posed with this question, I was then convinced by the claim that the very constraints of written text—the same ones that lend to this “perverse” disjunction—may also serve to be ample grounds for creative and critical thought. Within this very first portion of the book I saw what I thought to be the riveting soul of live coding: a performance practice that both works within and challenges the limitations of the media used (whether it be the computer used to code or even the book used as a manual).

Another idea that stood out to me was the identity and presence of the “user.” Much of the definition of live coding hinges the presentation of this live conversation held between the user and the machine. I was particularly struck by the part of the text in which the artist Olia Lialina was invoked to discuss the disappearance of the user. The mention of “smart” products and how “Big Tech wants computers to be invisible so our experience of using them becomes seemingly natural” thus goes in tandem (or rather, at odds with) how live coding may be seen as an ideologically potent practice that directly fights against this (corporate) trend to bring the user—and the computer—back into the visible foreground (or even existence) It then does not seem to be merely coincidental that the very title of the book describes itself as “A User‘s Manual.”