My artistic journey began with generative art, a creative practice rooted in the idea that mathematical expressions could produce visual patterns and imagery. I worked primarily with Processing, an open-source Java-based programming language and environment for creative interactive practices. I applied to the Academy of Media Arts Cologne with my project Sun1, programmed in p5.js, a JavaScript-based variation of Processing that runs directly in the web browser. The project explores the invisible yet tangible byproduct of computation: heat. Microchips generate heat due to electrical resistance and the inherent inefficiencies of electronic components (energy lost as warmth).
In Sun, I programmed a visual system composed of orange gradient particles that slowly accumulate into the glowing, flickering form of a sun. As any device continues to run the program, it inevitably generates heat; I attempt to highlight the blurred boundary between the digital and the physical, simulating a "leaking" heat from the interface to provoke a warm sensation in reality. Although the intention was to explore how digital images connect through interfaces, in retrospect, the project also underscores how material conditions ground digital image-making. Heat is pervasive in every electronics stage, from resource extraction and lithographic processes on silicon
This exploration prompts my interest in AI image-making, both literally and conceptually. Images possess the power to conjure memories, provoke emotions, and facilitate communication between artists and audiences. Over recent decades, the process of creating images has been thoroughly digitized, with computers routinely enhancing and altering visuals through filters, textures, and layering techniques. Generative AI now introduces a radically new way of image-making that raises questions about what it means to create and perceive an image.
Throughout the journey of working with generative art, the challenge of generating sophisticated images often requires an advanced understanding of algorithms. I discovered that incorporating image processing techniques significantly enriched the textural variation of the visuals. Images that were bounded by reality hold more information than digitally drawing complex lines on an imaginary black canvas. As practices evolved, I encountered the intriguing phenomenon of generating images with AI solely from textual descriptions. This became the initial idea of the project Imaginary Landscape2, where I utilized AI-generated images as the source for conventional generative audio-visuals. After generating thousands of landscape images, I used Processing for image interpolation and applying shader effects.
This exploration prompts my interest in AI image-making, both literally and conceptually. Images possess the power to conjure memories, provoke emotions, and facilitate communication between artists and audiences. Over recent decades, the process of creating images has been thoroughly digitized, with computers routinely enhancing and altering visuals through filters, textures, and layering techniques. Generative AI now introduces a radically new way of image-making that raises questions about what it means to create and perceive an image.
Commercial discourse often describes AI-generated images as "useless tools." With its lack of understanding of real-world physics and inconsistencies in transformations, it apparently lacks immediate profitability or practical application. Nevertheless, AI-generated images offer an infinite reservoir of visual material akin to an extensive yet blurred search engine result. These visuals are ideal for further experimentation and manipulation through advanced image-processing techniques, functioning as raw material for artistic exploration.