The Winding Road to Better Machine Learning Infrastructure Through Tensorflow Extended andKubeflow
When Spotify launched in 2008 in Sweden, and in 2011 in the United States, people were amazed that they could access almost the world’s entire music catalog instantaneously. The experience felt like magic and as a result, music aficionados dug in and organized that content into millions of unique playlists. Early on, our users relied on playlists and rudimentary recommendation features like a related artists feature to surface new music.
Over time Spotify got more advanced in our recommendations and user-favorite features like Discover Weekly started to significantly improve new music discovery and the overall Spotify experience (more on that journey in this talk). More users and more features led to more systems that relied on Machine Learning to scale inferences across a growing user base.