Artificial Intelligence could put a bunch of composers out of work—and transform the way we make music.
Ed Newton-rex grew up immersed in music. As a child, he sang in the King’s College Choir in Eng land and played piano. He went on to earn a music degree, and one of the things he studied was, “Why do people like music?” he told me. The answer, he learned, is that there’s no simple answer: It’s a deeply complex stew of art, timbre, and emotion.
And math. As Pythagoras discovered about 2,500 years ago, music is deeply mathematical, and it’s possible to represent melody using numbers and ratios. After finishing his undergraduate degree in 2010, Newton-Rex went to visit his girlfriend, who was studying at Harvard. He sat in on a coding lecture and became enraptured with the idea of writing software that could generate songs by harnessing the machine’s ability to semi-randomly recombine numbers. “Why haven’t computers been able to do this yet?” he wondered.
Over the next year, he set out to create a composing machine. He taught himself enough to code up a prototype that would create songs based on a set of simple rules. Before long, his system, Jukedeck, was cranking out instrumental tunes good enough to convince some investors to back him. He then hired programmers to rebuild his system using “deep learning” neural networks, the hot new artificial-intelligence technique. Neural nets can, in effect, learn on their own. Newton-Rex would feed thousands of melodies his team composed—pop, blues, folk, and other genres—into the system. The neural net would decode the deep patterns in the music and crank out new melodies based on what it had intuited.
This story is from the March/April 2019 edition of Mother Jones.
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This story is from the March/April 2019 edition of Mother Jones.
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