Introducing the primary model for contextualizing ancient inscriptions, designed to assist historians higher interpret, attribute and restore fragmentary texts.
Writing was all over the place within the Roman world — etched onto every thing from imperial monuments to on a regular basis objects. From political graffiti, love poems and epitaphs to business transactions, birthday invitations and magical spells, inscriptions offer modern historians wealthy insights into the range of on a regular basis life across the Roman world.
Often, these texts are fragmentary, weathered or deliberately defaced. Restoring, dating and placing them is sort of unattainable without contextual information, especially when comparing similar inscriptions.
Today, we’re publishing a paper in Nature introducing Aeneas, the primary artificial intelligence (AI) model for contextualizing ancient inscriptions.
When working with ancient inscriptions, historians traditionally depend on their expertise and specialized resources to discover “parallels” — that are texts that share similarities in wording, syntax, standardized formulas or provenance.
Aeneas greatly accelerates this complex and time-consuming work. It reasons across hundreds of Latin inscriptions, retrieving textual and contextual parallels in seconds that allow historians to interpret and construct upon the model’s findings.
