By Paul McGowan From PS Audio

When we flip through some of the more mainstream streaming services like Netflix, Pandora, Spotify, and Apple Music, we’re often not surprised when they make recommendations to us that fit our profile. I stream a weird combination of opera, jazz and dance music, yet the recommendations for me on Spotify line up pretty well at times.

Machine learning using comparative data strings is becoming increasingly commonplace in our artificial intelligence centric world. I note that the music server Roon is dabbling in a version of this based on their connected community. PS Audio did the same thing nearly a decade ago with our PerfectWave Transport and its online cover art library.

While this trend towards automation and relying upon machines for this work might seem new and novel, the basic ideas of how music gets recommended is as old as distributed music itself. In the earliest days of recorded music, record stores featured the most popular selling discs. Move forward to radio and you’ll find DJs and music directors playing “the hits”. Today, we share our favorites via forums.

Sharing and recommending movies and music is a valuable community endeavor regardless of how the data is gathered, organized, and distributed.

Music is meant to be shared.

For more on this story go to: https://www.psaudio.com/pauls-posts/recommended-music/