Recently, during an online discussion about generative art, determinism, emergence, and the like, I felt like we were running in circles. The problem seemed to be different interpretations of “predictability” and it’s relationship to determinism.
From my very first steps with processing, I’ve always been fascinated by the division of space, volumes and surfaces. In retrospect, many of my constructs can be seen as explorations of this theme.
I’ve spend some time delving into my shelves to collect the books that shaped my creative coding practices. Some of them I wholly internalized, others…
Spaghetti code is great! For many of us writing creative coding in Processing, starting with a simple idea and progressively adding layer and layer of complexity and functionality is a familiar workflow. It’s also a source of unexpected emergent features, what others would call bugs or mistakes *eyeroll*. The tangled messes we code…
This year, I was given a most wonderful Father’s Day gift, a draft, technical pen on tracing paper, that my father made in 1960 as part of his graduation as a “technisch ingenieur”, industrial engineer.
Ages ago, 2006 or so, I came across a small book, Pamphlet Architecture 27: Tooling by Benjamin Aranda and Chris Lasch. It described several generative, parametric systems. One of the recipes is shown here, cracking. In this post we’ll build a generative system in Processing to explore the idea.
The last few months, I spent quite some time in one-on-one conversations on Twitter and Instagram with people looking for help on something they want to try with creative coding. Often, these conversations start with the same questions, what courses to follow, what books to read, what learning path to follow?
Signed distance functions (sdf) are a staple of shader and raytracing code. This article shows a way to abuse sdfs for fun and profit*.
*mileage may vary