A group of researchers, co-led by researchers from Google DeepMind and the University of Nottingham, have launched a world-first AI model that can contextualise ancient inscriptions.
The research, published today in Nature, explains how Aeneas, the AI model, could greatly reduce the workload of researchers and draw connections from a wide range of historical evidence.
When working with ancient inscriptions, historians traditionally rely on their expertise and specialised resources to identify ‘parallels’ - texts that share similarities in wording, standardised formulas or provenance.
Aeneas greatly accelerates this complex and time-consuming work. It reasons across thousands of Latin inscriptions, retrieving textual and contextual parallels in seconds that allow historians to interpret and build upon the model’s findings.
The model can also be adapted to other ancient languages, scripts and media, from papyri to coinage, expanding its capabilities to help draw connections across a wider range of historical evidence.
Google DeepMind co-developed Aeneas with the University of Nottingham, and in partnership with researchers at the Universities of Warwick, Oxford and Athens University of Economics and Business (AUEB). This work was part of a wider effort to explore how generative AI can help historians better identify and interpret parallels at scale.
To train Aeneas, the research team curated a large and reliable dataset, drawing from decades of work by historians to create digital collections. They cleaned, harmonised and linked these records into a single machine-actionable dataset, referred to as the Latin Epigraphic Dataset (LED), comprising over 176,000 Latin inscriptions from across the ancient Roman world.
Aeneas helps historians interpret and contextualize a text, give meaning to isolated fragments, draw richer conclusions and piece together a better understanding of ancient history.
The model’s advanced capabilities include: