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Neural issue # 37 came with a booklet on Zachary Lieberman's workshop at Fabrica. Here Lieberman asks the question: "How can we use code to create real-time animation that is lifelike and organic?" Back in 1986 Craig Reynolds gave one answer to this question. His “Boids” algorithm, which simulates the motion of flocks of birds and schools of fish, is one of the most frequently employed methods to camouflage silicon-based processes as carbon-based ones. Quiet Ensemble have a different proposition, which suggests that life is the best model of itself. In their work Quintetto, developed together with Fabio Sestili, five goldfish swim in five separate fish tanks. The tanks are so flat and thin that they appear almost as two dimensional as a computer screen. The movement of the fish is captured with a video tracking system and the acquired data is used to feed a number of sound synthesis units. The result resembles a generative audiovisual piece, but there is something in the arbitrary decisions of five goldfish that appears to have a different quality than the seemingly similarly random decisions of an algorithm. Even though the authors are here definitely outsmarting their performers, it transpires that using real specimens can be more compelling than coding simulations.
Matteo Marangoni
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Quintetto, sounding goldfishes
Neural issue # 37 came with a booklet on Zachary Lieberman's workshop at Fabrica. Here Lieberman asks the question: "How can we use code to create real-time animation that is lifelike and organic?" Back in 1986 Craig Reynolds gave one answer to this question. His “Boids” algorithm, which simulates the motion of flocks of birds and schools of fish, is one of the most frequently employed methods to camouflage silicon-based processes as carbon-based ones. Quiet Ensemble have a different proposition, which suggests that life is the best model of itself. In their work Quintetto, developed together with Fabio Sestili, five goldfish swim in five separate fish tanks. The tanks are so flat and thin that they appear almost as two dimensional as a computer screen. The movement of the fish is captured with a video tracking system and the acquired data is used to feed a number of sound synthesis units. The result resembles a generative audiovisual piece, but there is something in the arbitrary decisions of five goldfish that appears to have a different quality than the seemingly similarly random decisions of an algorithm. Even though the authors are here definitely outsmarting their performers, it transpires that using real specimens can be more compelling than coding simulations.
Matteo Marangoni
email this | + facebook | + twitter | TrackBacks (0)
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