The wave of exciting new AI demos & applications over the past year has highlighted a familiar engineering challenge: Beyond prototypes, how can we ensure that we can improve our systems rapidly, & maintain them without too many headaches, recognizing the amount of real-world complexity involved? While the question is not new, it has been exacerbated by the presence of data & rapidly evolving ML.

Our talk will delve into this, focusing on a unique feature of ML systems—they're not isolated islands but deeply intertwined with their surrounding environment, responsive to real-time changes. We'll draw from our experiences at Netflix to explore a practical, user-friendly approach to composing & orchestrating advanced ML systems.

We'll discuss our solution, Metaflow, an open-source ML platform we developed at Netflix, which now powers thousands of ML projects at 23&Me, Disney, Goldman Sachs, Sanofi, etc., & Argo Workflows. We'll highlight our recent work that builds on top of Argo Events.