Generative algorithm using machine learning (GAN, T-SNE) and fluid simulation (Navier Stokes), user profile data caches (DNA, fitness, and dating), Ferrofluid, custom electromagnet matrix, custom PCB control system, computer, steel, elastomer, wood, aluminum
courtesy the artist, TARO NASU, Ishikawa Foundation and with support from Cornell Tech, \Art
In New Humans, emergent gatherings of synthetic humans rise from the surface of a black ferrofluid pool. Appearing to morph like a supernatural life form, these dynamic clusters of magnetic liquid produced by machine learning process are images of communities of synthetic people — hybrid profiles modeled from actual DNA, fitness, and dating profile data sets sourced from public and leaked caches. The work questions how we can radically conceptualize the “user profile” to embody a self whose bounds are indefinable and multiple.
Brooklyn Research worked with Mika Tajima to develop the hardware solutions and communication protocol for this piece. And worked closely with the team in Okayama, Japan to assist with installation of the piece.