A clear temptation for the future: learn JavaScript properly and work with the browser. Various causes to this idea, and one I would like to stress now is the presence of the RiTa Library, a set of tools for text analysis and generation in JavaScript, which could be an excellent excuse for:

  1. Getting into JS in the first place;
  2. Move toward a routine based on small incremental projects;
  3. A nice way of practicing my NLP tools (alongside NLTK in Python).

What is more, the unstoppable Dan Shiffmann dedicated the past few years to JavaScript for creative coding, leading to a flurry of tutorials and resources, e.g. this one on RiTa:


I should add that Shifman is at this very moment developing a series of tutorials introducing TensorFlow.js, anticipating the irruption of ever easier machine learning libraries for creative purposes:


Methodology / Tetralogy

An idea that came to me would be to follow Lior Ben-Gai’s methodology for his course ‘Programming for Artist II’ (which unfortunately clashed with another course I took last term), in which he distributed possible projects/assignments into four categories:

  • Random (using the built-in random function(s) in the programming language of your choice, which in this case was Processing);
  • Functional (adapt a mathematical concept, e.g. the Calabi–Yau manifold, but it could be any other idea taken from the sciences, for instance Markov models for text?, to a creative project of your choice);
  • Data-driven (use a dataset as a basis for your project);
  • Emergent (devise simple rules appyling to agents or objects and study the result of having many of these ‘evolving’ or ‘acting’ together, as can be seen in flocking or other systems, focussing on the consequences of a bottom-up form of artistic organisation).