ADeLe: Predicting and explaining AI performance across tasks

Researchers from Microsoft, Princeton University, and Universitat Politècnica de València have developed ADeLe, a method that evaluates AI models by scoring both tasks and models across 18 core abilities, predicting performance on new tasks with about 88% accuracy. This tool is crucial for developers and tech professionals as it provides detailed insights into model strengths and weaknesses, enabling better anticipation of potential failures before deployment. Future developments may extend ADeLe to multimodal AI systems and standardized research frameworks.

Read the full article at Microsoft Research

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