FROM NOISE TO FORM: DESIGN METHODOLOGIES FOR CYBORG NATURES
Historically, humans have emulated living beings through imagination, storytelling, religion, science, and technology. By copying the behavior of the brain’s neurons, the first neural network was developed—technology that can teach itself and improve over time with minimal to no human intervention. For the past century, biomimicry has been integral in this emulation process in Art, Design and Technology, relying on the artist, designer, and engineer to study and copy the mechanisms found in Nature
What does it mean to be inspired by Nature when we live in artificial and cyborg landscapes?
What new design methodologies can we develop in this techno-ecology?
What does it mean to be inspired by Nature when we live in artificial and cyborg landscapes?
What new design methodologies can we develop in this techno-ecology?
Project led by Anastasiia Raina, working in collaboration with AI Researcher Lia Coleman, Yimei Hu, Danlei Elena Huang, Zack Davey, and Qihang Li
One of our ML experiments “failed” by an accidental deletion of the datasets. Somehow, this program kept running with no pixels to compare, and this collapse led to a beautiful indescribable form.
Could this be what a machine sees?
The organic form seen above responds to its environment. The points to the left are (x,y,z) coordinates of the where the audio source moves over time. Turning those into keyframes and using them as attractors, the form grows towards this spatial soundscape
Trained with StyleGAN 2 and dataset created by Elena Danlei Huang