Aeneas: an AI model for restoring and contextualizing ancient inscriptions.

4 August 2025
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Fragment of a bronze military diploma from Sardinia, issued by the emperor Trajan to a sailor on a warship. 113/14 CE (CIL XVI, 60, The Metropolitan Museum of Art, Public Domain).

A team of researchers, including Professor Jonathan Prag, has just published a paper in Nature introducing Aeneas, the first artificial intelligence (AI) model for contextualizing ancient inscriptions. 

Aeneas transforms how historians connect the past, offering the first model for contextualizing ancient inscriptions, designed to help historians better interpret, attribute and restore fragmentary texts.

Writing was everywhere in the Roman world — etched onto everything from imperial monuments to everyday objects. From political graffiti, love poems and epitaphs to business transactions, birthday invitations and magical spells, inscriptions offer modern historians rich insights into the diversity of everyday life across the Roman world.

Often, these texts are fragmentary, weathered or deliberately defaced. Restoring, dating and placing them is nearly impossible without contextual information, especially when comparing similar inscriptions. 

When working with ancient inscriptions, historians traditionally rely on their expertise and specialized resources to identify “parallels” — which are texts that share similarities in wording, standardized formulas or provenance. 

Aeneas represents a concerted effort to bring the power of AI to bear on the complex uncertainties of humanities research. In a field of this sort, the answers are not black and white, and the data is simultaneously rich and incomplete. Aeneas takes a leap beyond Ithaca to provide humanities researchers with a level of support – based upon previous scholarship - that we could only previously have dreamed of.

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 research was co-led by Yannis Assael and Thea Sommerschield (a former DPhil student in the Faculty), bringing together a team from Google DeepMind which 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.

 “Aeneas represents a concerted effort to bring the power of AI to bear on the complex uncertainties of humanities research. In a field of this sort, the answers are not black and white, and the data is simultaneously rich and incomplete. Aeneas takes a leap beyond Ithaca to provide humanities researchers with a level of support – based upon previous scholarship - that we could only previously have dreamed of.”

Learn more about Aeneas