● Currently, the hottest area of development is to revolutionize music discovery and personalization.
● Spotify's approach, called collaborative filtering, is to collect as much data as possible on a user's listening behavior and then compare it to that collected from other users.
● Pandora takes a slightly different approach, deploying a combination of human expertise and algorithms. Music experts tag songs with hundreds of characteristics, from genre to tonality. The company's algorithm then matches these characteristics so that when a user selects a particular artist or song, a "radio station" of music with similar attributes is created.
● Still, to gain a competitive edge, the services are taking artificial intelligence a step further by investing in "deep machine learning." This technology offers greater promise for classifying music and making more accurate recommendations to users.
● Beyond music playlists, AI and machine learning are paving the way for other types of music applications.
○ For example, it's now possible for computers to write songs. Scientists at Sony's CSL Research Laboratory released the very first pop song composed by an artificial intelligence system called Flow Machines.
○ .Jukedeck, a London-based startup, offers unique, royalty-free compositions designed by algorithms and written in just seconds.
○ Another innovator, Brain.FM, is focusing on how music can be used to help individuals with ADD, anxiety and insomnia. Working with neuroscientists, they've created AI software for audio brainwave training, designed to improve focus, relaxation and sleep.
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