Vice reports on algorave music — algorithmically generated electronic dance music:
“I’m a live coder, and over the last ten years I’ve been writing code to try to make people dance. That’s my aim,” Alex said. Writing code to make music has been a decade-long interest for Alex and Nick, but the epiphany to transport it into a club environment didn’t come along until a couple of years back. “Nick and I were driving up to Nottingham for an event, and we tuned into a pirate radio station called Rogue FM,” Alex said. “DJ Jigsaw was on, playing loads of happy hardcore, and that sort of influenced our set that night. At that point, it became algorave.”
By their own description, “Algoraves embrace the alien sounds of raves from the past, and introduce alien, futuristic rhythms and beats made through strange, algorithm-aided processes.” Alex attempted to breakdown the function of live coding in simplistic terms: “It’s a bit like making a knitting pattern or something; you come up with this usually quite simple way of describing patterns—this is my approach—and then use this as a sort of language for describing your music.”
So how exactly is Python programming useful in creative writing? Parrish’s course doesn’t deal with artificial intelligence, or attempts at creating narratives or creating interactive hypertext or anything like that. It covers, for lack of a better term, procedural poetry. Typically, a student takes a starting set of text, writes a Python program to modify that text and then interprets the results.
Parrish cited non-electronic procedural poetry experiments as inspirations for the course. For example, he talked about Raymond Queneau’s Cent mille milliards de poèmes, a book in which the text has been cut into strips that can be re-arranged to create nearly endless configurations:
Parrish also mentioned Ted Berrigan’s Sonnets and David Melnick’s PCOET. Parrish didn’t mention them in his talk, but the course website also mentions Brion Gysin and William S. Burroughs’ work with the cut-up technique.
Shapeways has a round-up of evolutionary, algorithmic & generative design projects, including the “cellular bowl” above, designed with Processing.
The marriage of tech and design is all around us. In a world where everything is designed a meta “way to design” that algorithmically cuts through the clutter is very appealing. A perfect design algorithm could potentially engender choice in design the same way that Google’s PageRank set of algorithms do for the web. And this is what generative design already partially does. It simplifies design by codifying it and somewhere within lies the promise of “true”, “simple” & “beautiful” design.
With technologies such as 3D printing letting everyone design or co-design things there is also a real need for generative tools. They allow for unique designs but since each is machine made, the marriage is a conceptually comfortable and inexpensive one. Also, rather than forcing the customer into a “blank canvas conundrum” whereby the sheer possibility overwhelms them to the point inactivity, generated models could lead to choice or guided choice in design.