The history of art has seen significant shifts in the manner in which artworks are created, making understanding of creative processes a central question in technical art history. In the Renaissance and Early Modern period, paintings were largely produced by master painters directing workshops of apprentices who often contributed to projects. The masters varied significantly in artistic and managerial styles, meaning different combinations of artists and implements might be seen both between masters and within workshops or even individual canvases. Information on how different workshops were managed and the processes by which artworks were created remains elusive. Machine learning methods have potential to unearth new information about artists' creative processes by extending the analysis of brushwork to a microscopic scale. Analysis of workshop paintings, however, presents a challenge in that documentation of the artists and materials involved is sparse, meaning external examples are not available to train networks to recognize their contributions. Here we present a novel machine learning approach we call pairwise assignment training for classifying heterogeneity (PATCH) that is capable of identifying individual artistic practice regimes with no external training data, or "ground truth." The method achieves unsupervised results by supervised means, and outperforms both simple statistical procedures and unsupervised machine learning methods. We apply this method to two historical paintings by the Spanish Renaissance master, El Greco: The Baptism of Christ and Christ on the Cross with Landscape, and our findings regarding the former potentially challenge previous work that has assigned the painting to workshop members. Further, the results of our analyses create a measure of heterogeneity of artistic practice that can be used to characterize artworks across time and space.

Have you ever wondered what famous historical paintings would look like if they were created today? Thanks to the power of artificial intelligence (AI), it's now possible to reimagine these masterpieces in ways that were previously impossible. Using advanced algorithms like those found in Midjourney v5, AI can analyze and manipulate existing artwork to create new and innovative pieces. For example, AI can be used to alter the color palette or style of a painting, giving it a modern twist while still maintaining the essence of the original work. Let's take a closer look at how AI can be used to reimagine these famous paintings: The Persistence of Time is a surrealist masterpiece that is famous for its melting clocks.

Google has launched a new feature that lets you find your pet's lookalike in historical paintings. The tool is part of the company's "Arts and Culture" app and uses artificial intelligence to scan to see whether anyone has painting an animal that looks like the one in your house. It could pick out pets in everything from ancient Egyptian figurines to Mexican street art, Google said, as a result of its partnerships with a variety of institutions around the world. The feature will work on dogs, cats, fish, birds, reptiles, horses or rabbits, Google says. To use the feature, users just download the app and submit their picture.