The Evolution of AI in the Music Industry: From Composition to Curation

The History of AI in Music Composition

Artificial intelligence (AI) has been making waves in the music industry for several years now. From composition to curation, AI has been used to create music, analyze it, and even recommend it to listeners. But how did AI come to be such a powerful tool in the music industry? Let’s take a look at the history of AI in music composition.

The first attempts at using computers to create music date back to the 1950s. However, these early attempts were limited by the technology of the time. It wasn’t until the 1980s that AI began to make significant strides in music composition.

One of the earliest examples of AI music composition was the program called Experiments in Musical Intelligence (EMI), created by David Cope in 1981. EMI was designed to analyze existing pieces of music and then create new compositions based on that analysis. The program was able to create music that was similar in style to the original pieces it analyzed, but with its own unique twists.

In the years that followed, other AI music composition programs were developed, including the Continuator, which was created by François Pachet in 2003. The Continuator was designed to create music in real-time, responding to the input of a human musician. This allowed for a more collaborative approach to music creation, with the AI program serving as a sort of musical partner.

As AI music composition programs continued to evolve, they became more sophisticated and capable of creating music that was increasingly complex and nuanced. In 2016, the first AI-generated pop song was released by the program Amper Music. The song, called “Break Free,” was created using algorithms that analyzed existing pop songs and then generated a new song based on that analysis.

Today, AI music composition programs are being used by musicians and composers around the world. These programs are able to create music that is both unique and familiar, drawing on the vast library of existing music to create something new and exciting.

But AI’s role in music composition is just the beginning. In recent years, AI has also been used to analyze and curate music.

One example of this is the music streaming service Spotify, which uses AI algorithms to recommend music to its users. The algorithms analyze a user’s listening history and then recommend new music that is similar in style or genre. This has helped to introduce listeners to new artists and genres that they may not have discovered otherwise.

Another example of AI in music curation is the program called The Sync Project, which was created by Marko Ahtisaari in 2015. The Sync Project uses AI to analyze the effects of music on the human body and mind, with the goal of creating personalized playlists that can be used to improve health and well-being.

As AI continues to evolve, its role in the music industry is likely to expand even further. From composition to curation, AI is helping to shape the way we create, listen to, and experience music. And with new developments and innovations on the horizon, the future of AI in music is sure to be an exciting one.