IN THE LOBBY of the Museum of Modern Art stands a 24-foot-tall screen that emits a continuous flow of psychedelic slush and bacterial blobs. People stare, dance, and make Instagram reels in front of it, as an electronic score plays and pulpy Nerf shapes splash over its trompe l’oeil edges. The whole thing looks like a massive techno lava lamp. This is Refik Anadol’s Unsupervised, some cross between relaxation exercise and euphoric TED Talk and NSA levels of data mining. It’s a smash success.
With the help of a 15-person studio, the Turkish-born, Los Angeles–based Anadol has used artificial intelligence to reinterpret the metadata that comprises the online database of MoMA’s immense collection. That’s 138,151 records, according to the museum, “freely available on GitHub.” The results are cool patterns that recall digitized versions of van Gogh paintings morphing into paintings that look like Monet’s, which then turn into de Koonings or Frankenthalers or Rothkos, into sandstorms and mashed potatoes and other things that sort of look like art. These are interspersed with sequences that look like charts, diagrams, waves, and other amorphous stuff. It all adds up to a narcotic pudding. Just as we have smart appliances to monitor steps, heart rate, and sleep patterns, so are we now scanning museum collections. Call it search-engine art—a new dataism that programs the history of modernism so we can see everything all at once.
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