Spotify AB is making the most out of the $1 billion in debt financing it raised last year.

The music streaming giant quietly revealed Wednesday that it has bought Niland, a Paris-based machine learning startup, in what marks its fourth acquisition since the beginning of the year.

Spotify has previously picked up blockchain database maker Mediachain Labs Inc. and two firms that focused on developing tools for automatically processing multimedia content. Like Niland, the latter startups based their offerings on artificial intelligence, which suggests that the technology is emerging as a major priority for Spotify.

The French startup will help bolster its push by bringing a specialized recommendation engine to the table that can identify the key elements of a track and find similar content. According to Niland, its software breaks down each song into “several thousand dimensions” to produce more accurate comparisons than alternative offerings. This approach has enabled the system to win the MIREX music analysis competition every year since 2011.

Niland’s technology could help boost the track recommendation features at the center of Spotify’s plans to stand out from Apple Music and other rivaling streaming services. The provider offers a tool called Release Radar that produces a personalized selection of new releases for users every week, as well as an automatic playlist generator that has attracted 40 million listeners within its first year.

Any future features that Spotify may develop using AI could also benefit from the acquisition of Niland. The deal brings aboard an experienced team of machine learning researchers who have spent years exploring how the technology can be applied to processing music. They will move to the streaming provider’s New York office as part of the acquisition.  

In the long run, the expertise that Spotify is gaining through the purchase of Niland could prove just as valuable as its technology. There’s so much competition over AI talent that even the world’s largest tech firms are struggling to meet internal staffing requirements. Facebook Inc., for instance, is running deep learning workshops for employees because of the difficulty of finding outside talent. 

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