While fascinating, the conceptual approach to Blossoms naggingly skirts the obligatory or novel. Yet there is a disheveled acclimation that occurs with the music produced by this experiment. Perhaps around the third track (a decidedly rubbery post-nasal drib, oddly titled “Bloom”), there’s a sour and smudgy trance that settles around the head, like watching a sordid b-movie in slow blinks.
Moving from two releases created entirely with homemade instruments, including the acoustic EP Skin, experimental duo Emptyset took a more scientific approach with their 2019 full-length. Blossoms was conceived using a neural network-based artificial intelligence system. Emptyset's James Ginzburg and Paul Purgas spent 18 months developing a machine learning system with a network of programmers, and they supplied the system with several hours of music improvised on their own unique instruments, as well as some of the duo's previous recordings.
Early one morning in February 1966, Cleve Backster was alone in his office at the Backster School of Lie Detection, drinking coffee and thinking about setting his secretary's Dracaena cane plant on fire. During normal business hours at the school, Backster taught NYC police and FBI agents how to administer polygraph tests - knowledge gleaned from his work with the Counter-Intelligence Corps during WWII, and later as an interrogation specialist for the CIA, where he introduced the use of lie-detection machinery. But after pulling an all-nighter in his office, Backster found himself wondering: "Would this plant respond like a human does if I hooked it up to a polygraph machine? What would happen if I set one of its leaves on fire?" This is the story that came to mind during my first listen to Emptyset's Blossoms - the duo's second LP on Thrill Jockey, and latest in a series of delightfully raw and rackety releases produced over the course of a decade.