Just two days later, the Financial Times reported that YouTube is pursuing a comparatively above-board approach. Rather than training AI music models on secret data sets, the company is reportedly offering unspecified lump sums to top record labels in exchange for licenses to use their catalogs for training data. While the ground here is moving fast, none of these moves should be all that surprising: litigious training-data battles have become something like a rite of passage for generative AI companies. The trend has led many to pay for licensing deals while the cases unfold. But the stakes of a fight over training data for AI music are different--and arguably even higher.

With the success of Peter Jackson's Get Back, the documentary streaming on Disney Plus, Beatlemania is back. Watching Paul McCartney create the eponymous song out of seemingly nothing, as George Harrison stands nearby yawning, is one of 2021's cinematic pleasures. The Beatles are arguably the most successful pop group in history and, in the years since their heyday, countless artists, producers and songwriters, not to mention record companies and now music streaming services, have tried to recreate the same magic. The latest tool for capturing elusive pop music gold is artificial intelligence. Usually when we think of artificial intelligence creating art, it's making something bizarre or unintentionally hilarious. Take Google's horrifying Deep Dream with its thousands of dog eyes, or Sunspring, a movie written by an AI that was fed hundreds of sci-fi scripts.

If you've ever played a YouTube video for what it seems like the thousandth time to listen to your instrument's part of a composition, you'll love MIT's new AI. PixelPlayer, which hails from the institution's Computer Science and Artificial Intelligence Laboratory (CSAIL), can recognize instruments in a video, identify specific ones at pixel level and isolate the sounds they produce. If there are several instruments playing in a video, for instance, PixelPlayer will allow you to pick the one you want to listen to -- it will play the sounds coming out of that instrument the loudest and will lower the volume or everything else. CSAIL trained PixelPlayer by using a self-supervised deep learning technique and feeding it over 60 hours of videos to learn from. It's still far from perfect, though: it can only identify the sounds of 20 instruments at the moment and is still having trouble telling similar ones apart.