Vassilis Digalakis, Ramayya Krishnan, Gonzalo Martin Fernandez, Agni Orfanoudaki
ML Compass is a framework that helps organizations choose AI models by balancing user utility, deployment costs, and compliance requirements, rather than just capability rankings.
Choosing the best AI model for an organization involves more than just looking at which one performs the best on a leaderboard. ML Compass is a new framework that helps organizations make these decisions by considering the trade-offs between how well a model performs, how much it costs to deploy, and whether it meets compliance requirements. This approach provides a more practical guide for deploying AI models in real-world scenarios, such as conversational systems or healthcare, by focusing on the specific needs and constraints of each application. The framework can lead to different recommendations than simply choosing the top-performing model, as it factors in additional considerations like cost and compliance.
