Manuel Delanda

I

have just started my PhD and have begun reading all those 1990’s books on how to do a PhD. Filled with useful advice like: when searching for a girlfriend, make sure she has transferable skills so that when you get employed overseas she can easily move with you; and start your research by phoning people in your area and asking them to post you papers. It is scary how much researching has changed in the last decade as information become freely accessible. I read almost everything as a pdf on the screen, downloaded from databases like CuminCAD. I get more fiction from the library than non-fiction (although most writing on architecture is fictitious). I have also been watching a bunch of lectures on Youtube by everyone from Steve Jobs to Neil Leach to Einstein to Manual DeLanda. In the 1990’s, only societies elite would have access to this information, now anyone with an Internet connection can watch Manual DeLanda deliver a lecture at Columbia University.

DeLanda’s lecture on Deleuze and the Use of the Genetic Algorithm in Architecture is a favorite of mine, for DeLanda’s stage presence as much as anything – no Powerpoint just an hour long rant without any cues. The lecture goes with a paper Delanda produced of the same name. To me, and the Youtube commenters, the philosophy DeLanda presents is a little dubious [i]. I wish he would throw it away like he has done to the Powerpoint and tell it straight because DeLanda, who was once a computer programmer, has a very good understanding of this subject. So since DeLanda wont and because an hour is a long time to watch Youtube, my summary of important points:

1. We have already used the genetic algorithm to design, most domestic animals are the result of selective breeding.
2. The genetic algorithm is a tool – although this somewhat contradicts DeLanda’s paper where he talks about architects becoming racehorse breeders, subservient to the code.
3. The genius of form can either be fixed, if it comes from a God like vision. Or it can be fluid if it comes from an evolutionary paradigm
4. Difference is critical to the process, and this corresponds to the paper where he says surprising results are important. If we are setting up genetic algorithm to produce homogenized shapes in a narrow range then why not just design them ourselves.