Not really knowing what to talk about, I decided to take a gamble. What better way to discuss creative coding than using Processing to build the entire presentation. This holds the risk of a crash-and-burn-with-audience. On the other hand, the alternative would've been Powerpoint. For a crowd of design-savvy individuals, a burning wreck is probably preferable.
For what it's worth on its own, I've put it online. It's a demonstration of the HE_Mesh library built around the theme of surface division and space partitioning. The title Division, The wrong way to draw a grid was inspired by Matt Pearson's upcoming book Generative Art: A Practical Guide Using Processing.
The core idea of the presentation is that the traditional, right way to define a grid, a collection of points and explicit connectivity, doesn't lend itself well to generative exploration. Modifying a grid while maintaining structural integrity requires extensive rulesets or hefty constraints. In my experience the code will turn out to be rigid and predictable. In another context this might be desirable. But generative and parametric algorithms differ from traditional art techniques.They are not meant to execute an idea, rather they should be tools to inspire and give new ideas.
I present two alternative approaches to a grid. Slides 4 to 10 handle the grid as a surface or volume divided by planar slices. While we lose some generality, the advantage of this dual representation is that it doesn't break down under perturbation. The grid connectivity is implicitely defined by the slicing operations. We are completely free to devise rulesets without having to worry about integrity issues. The iterative construction technique, the surface or volume is divided into a growing collection of subsurfaces or subvolumes, opens new venues for further exploration by modifying the impact of each step.
Slides 11 to 16 expose a rather different approach. Constructs made with more or less global slicing operations are obviously geometric and hold little of the organic. Nature works on a local scale, bottom-up. The Voronoi construction of a grid reflects this locality. In a sense it's another dual representation, this time defined by a collection of control points. The points themselves can be generated by any of a huge number of conceivable methods:pure math, physical particle simulation, autonomous agents, external data ... The connectivity is implicitely defined by the process that generates the cells and handles noise in a robust way. Voronoi structures can also be easily nested, first generation cells further refined by local point configurations, adding another layer of depth. We humans have developed an acute sense of balance between the geometric and the organic. Voronoi divisions come pretty close to the sweet spot.
The image of the Giant's Causeway in slide 1 was taken from this site. Unfortunately it's not credited so I can't properly acknowledge the photographer. The Causeway is a beautiful example of structure created by division rather than growth. Philip Ball gives a marvelous exposé on its origins in the third part, Branches , of his trilogy Nature' Patterns. I heartily recommend getting the entire trilogy.
The image takes you to the Processing sketch itself. Use up and down to move from slide to slide. The slides typically respond to a mouse-click and/or the spacebar. Imagine some more or less coherent babble, invite some good friends over and you can relive the Share && Tell experience right there and then in your own living room!