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Notes from Industry
Compositional AI: The Future of Enterprise AI
AI/ML Mesh, integrating DataOps, MLOps, APIOps
Abstract. Enterprise adoption of AI/ML services has significantly accelerated in the last few years. However, the majority of ML models are still developed with the goal of solving a single task, e.g., prediction, classification. In this work, we will present the emerging paradigm of Compositional AI, also known as Compositional Learning. Compositional AI envisions seamless composition of existing AI/ML services, to provide a new (composite) AI/ML service, capable of addressing complex multi-domain use-cases. In an enterprise context, this enables reuse, agility, and efficiency in development and maintenance efforts.
This is an extended article of a recent keynote that I gave at the International Data Fusion Conference, Skolkovo, Russia, Mar 31, 2021. (youtube recording) (ppt)
Enterprise AI
Enterprise AI/ML use-cases are pervasive today. The enterprise use-cases can be broadly categorized by the three core AI/ML capabilities enabling them: Natural Language Processing (NLP), Computer Vision/Image Recognition and Predictive Analytics (summarized in the figure below).
