The Sequence Scope: Machine Learning at Spotify

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📝 Editorial: Machine Learning at Spotify

Building large machine learning (ML) architectures remains unexplored territory for most companies. Despite the massive adoption of ML frameworks and platforms, most companies still apply ML in constrained and relatively small-scale scenarios. As an industry, we are still figuring out the best practices for ML infrastructures that can run large numbers of ML models from experimentation to production. Not surprisingly, the best inspiration for large-scale ML architectures comes from technology giants that are running some of the largest ML infrastructures in the world. Companies like Uber, LinkedIn, Meta, and Airbnb have been very transparent about their architectures used to run ML workloads and have even open-sourced many of its components…