It was only a matter of time before artificial intelligence became our taste-maker, choosing for us what would be more suitable to listen to, by studying our listening habits. Behind the scenes of some of the most popular music-streaming services, artificial intelligence is hard at work like an automated DJ, deciding which songs listeners will enjoy.

The technology’s ability to learn from the listening habits of millions of users across millions of songs has made the software key for nearly every music-streaming service today.

But its job doesn’t stop there. A.I. is playing an increasing role in some of the more subtle challenges inherent in music streaming, like adjusting sound volumes and eliminating dead air.

The usual suspects, Apple Music, Spotify, Youtube and Amazon Music have all implemented these new processing features to great effect, giving listeners a more enjoyable vibe that suits them uniquely. In future this can lead to great new song recommendations, as AI siggests new artists you would not have known otherwise.

For example, Sonos, best known for its wireless audio speakers, in April debuted Sonos Radio, a streaming service that features third-party radio stations as well as the company’s first foray into original music programming. Machine-learning technology provided by a partner, Super Hi-Fi, helps with an important job: creating a smooth transition between songs.

Without it, listeners may end up being annoyed by huge differences in volume between one song and the next. For example, songs recorded in the 1970’s are often quieter than more modern songs, partly due to the recording techniques of that era and changing tastes in music.





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