The adoption of artificial intelligence and machine learning techniques is making research on historical artifacts and handwritten records faster and more efficient. Artificial intelligence (AI) and machine learning techniques are helping historians restore or recreate archaeological artifacts from photos of fragments. Ayellet Tal of Israel's Technion University said applying algorithmic techniques to historical research can improve AI's capabilities. AI models can be taught how to reverse the erosion process, predict what the original fragments looked like, and test whether fragments fit together. Said Tal, "We want to transform archaeology and we want to advance computer vision because these tasks are where current algorithms fail."

Uncovering evidence for historical theories and identifying patterns in past events has long been hindered by the labour-intensive process of inputting data from artefacts and handwritten records. The adoption of artificial intelligence and machine learning techniques is speeding up such research and drawing attention to overlooked information. But this approach, known as "digital humanities", is in a battle for funding against more future-focused applications of AI. "There is a lot of interest in digital humanities, but there is not a lot of money," says Ilan Shimshoni, professor of computer vision and machine learning at the University of Haifa in Israel, where he works on archaeological projects that include reassembling artefacts from photos of fragments. "If you want to do an analysis of Facebook you'll get much more money than if you want to look at ancient Greek artefacts." Archaeological puzzles may not seem as urgent as computer science projects in healthcare, finance and other industries, but applying algorithmic techniques to historical research can improve AI's capabilities, says Ayellet Tal, an archaeological and computer science researcher at Israel's Technion University.