Gustav Söderström: Catapulting Spotify to the Front of the AI Revolution
Generative Now | AI Builders on Creating the Future
From Curation to Recommendation: An Evolution in Spotify's Data Strategy
The training data for Spotify's recommendation system was initially derived from the billions of user-created playlists, which served as a form of inadvertent training data. This led to the realization that the curated playlists were excellent training data for recommendations, prompting an early investment in recommendation technology. The initial recommendations served as a support to curation, with the introduction of similar artist suggestions. As understanding of user preferences improved, the company transitioned from a curation-first approach to a recommendation-first strategy, coinciding with the development of technology. This pivot occurred before the 2015 machine learning wave, positioning Spotify as an early adopter in leveraging data for recommendation systems, while still allowing users to curate their own playlists.
