Accelerating scientific discovery with the common task framework

Abstract

We propose the common task framework as a mechanism for accelerating scientific discovery through collaborative machine learning. This framework establishes shared datasets, evaluation metrics, and benchmarks that enable the AI and scientific computing communities to jointly advance the state of the art in scientific machine learning. By creating common tasks analogous to those that have driven progress in computer vision and natural language processing, we aim to catalyze breakthroughs in applying AI to fundamental scientific problems.