physics-inspired metric
Machine learning enables physics-inspired metrics for analyzing art
An international research collaborative reports that a systematized AI analysis of artwork produced over the last millenium yields revealing information about historical evolutionary artistic trends. Additionally, the results map well to canonical concepts about styles and periods of art history. Art analysis is usually comparative, and has historically been conducted by individual researchers, which places constraints on the scale of studies. It is impractical for a single scholar to compare more than a handful of paintings at a time. However, in recent decades, a vast amount of historical artwork has been digitized and made freely available, enabling quantitative approaches to art analysis that were previously unfeasible, if not impossible.