Inscriptions are vital for understanding ancient societies, but their damaged or incomplete state has historically posed challenges, which Aeneas aims to address.

Prominent scholars like Mary Beard have praised Aeneas as potentially transformative, capable of democratizing access to ancient history and reshaping research practices.

Aeneas incorporates contextual information such as the historical period and geographic location to improve the accuracy of its restorations.

With a database of nearly 200,000 inscriptions and images of 5%, Aeneas is trained to analyze and provide insights into Roman texts, including decrees and epitaphs.

Aeneas creates a 'historical fingerprint' for each text, detailing content, language, origin, and parallels, facilitating deeper analysis.

The tool was developed in collaboration with epigraphy experts from institutions like the University of Warwick to ensure relevance and accuracy.

Google DeepMind has developed Aeneas, an AI tool designed to restore and contextualize fragmented ancient Latin inscriptions, significantly advancing the field of epigraphy.

Aeneas utilizes neural networks to analyze large datasets, enabling it to detect patterns and recover more historical information despite inherent limitations.

The AI can estimate the chronological date of inscriptions within 13 years and identify their Roman provincial origin with 72% accuracy, enhancing historical interpretation.

While Aeneas improves efficiency, it still requires human oversight to validate its suggestions, ensuring accuracy in historical research.

In tests, Aeneas outperformed traditional methods, dating inscriptions within 13 years of the correct answer and improving experts' accuracy when used collaboratively.

The project includes educational initiatives to promote AI literacy in historical studies, aligning with frameworks from the European Commission and UNESCO.