Archaeological ceramics are a valuable source of information for reconstructing the customs, exchanges and social relationships of ancient populations, as well as for dating archaeological contexts (Sinopoli 1991; Peroni 1994; Steiner and Allason-Jones 2005; Vidale 2007; Orton and Hughes 2013; Hunt 2016). However, in order to turn a ceramic fragment into a rich source of scientific information, a long process of study and elaboration is required: once recovered in an excavation, the ceramic fragment is washed, catalogued, drawn and made ready for publication through the preparation of tables and figures that allow its correct interpretation and comparison with other archaeological contexts. Archaeological drawing is a fundamental and well-established tool in archaeological practice, and new technologies and methods are emerging to automate, standardise and speed up this process as much as possible. An example of this is the LAD (Laser Aided Profiler - Demján, Pavúk, and Roosevelt 2023), a tool that allows ceramic fragments to be'drawn' quickly and accurately using a laser beam. Over time, however, many drawings were made by hand using traditional tools such as pencils and then had to be'inked' and made ready for publication. Traditionally, this post-process was done by hand with Indian ink, and nowadays digital drawing programmes are used. This process is however extremely time-consuming and can often discourage the publication of new contexts due to the difficulties in terms of time and resources needed for inking. Generative AI can help to achieve this task, using complex image translation operation. Today, AI is permeating business, creativity and everyday life (Elliott 2019; Le et al. 2020; Varghese, Raj, and Venkatesh 2022; Azatbekova

In archaeology, there are few watershed moments, when a technological breakthrough changes everything. But the invention of radiocarbon dating in the 1940s brought one such revolution, by providing a consistent, worldwide system for placing archaeological material in chronological order. A more-recent transformative innovation is the airborne application of a remote-sensing technique called light detection and ranging (lidar) to create a model (also known as a digital-elevation model) of the bare-surface terrain that is hidden by trees in forested areas1. Lidar is changing archaeological study of the ancient Maya in Mexico and Central America. It is increasing the speed and scale of discovery, and reshaping our understanding of the antiquity of monumental-scale landscape alteration.

Many of the problems of recognition and interpretation encountered in archaeology have close parallels with classic artificial intelligence problems, notably those of scene analysis.