Unsupervised — Data Universe — MoMA #1731

“Unsupervised — Data Universe — MoMA” is a global AI data painting that simulates a latent walk among the museum’s digitized collection. The artist and his team used MoMA archives to construct the seven dimensions of the artwork: x, y, z, r, g, b, and time. It combines Anadol’s vision of handling data within a universe that it creates for itself with his approach to data visualization’s latent space as a locus for never-ending, self-generating contemplation. Researcher Leland McInnes, the inventor of the UMAP technique that Anadol has used for “Unsupervised — Data Universe — MoMA” wrote, “I have always found beauty in mathematics, but to see what Refik has done with mathematics and these algorithms to create art is something else again: bringing together rich threads of information and data to weave amazing visual works. I never imagined that my work in mathematics could have such far reaching impacts.”