Conor Griffin’s Post

📜 Today, we’re publishing our latest work in Nature: Aeneas, the first AI model for connecting the past. Ancient inscriptions often lack context – it's like solving a puzzle with 90% of the pieces lost to time. Aeneas helps researchers interpret and situate inscriptions in their past context. By transforming each ancient text into a unique historical fingerprint, Aeneas can identify similarities across 176,000 Latin inscriptions. In our study, historians found these ‘parallels’ to be helpful research starting points 9 out of 10 times - improving their confidence by 44%. We tested Aeneas on the Res Gestae Divi Augusti – one of the most debated ancient inscriptions. Without prior knowledge, it successfully mapped out the leading scholarly theories on its dating, showing how AI can help model history in a quantitative way. 📊 Aeneas is now accessible through: 👉 A website for researchers https://lnkd.in/dbbVfJDE 🏛️ Upgraded Ithaca ancient Greek model 🧑💻 Open-source code and dataset https://lnkd.in/duRutiNq 📚 Syllabus for teaching AI & History in classrooms https://lnkd.in/dQPZHKgA 🚀 Thank you all for making this possible! Thea Sommerschield, Alison Cooley, Brendan Shillingford, John Pavlopoulos, Priyanka Suresh, Bailey Herms, Justin Grayston, Benjamin Maynard, Nicholas Dietrich, Robbe Wulgaert, Jonathan Prag, Alex Mullen & Shakir Mohamed We’re excited to see how more people use this work to uncover the past. Find out more: - https://lnkd.in/dvRJ9nhz - https://lnkd.in/dTtSqaCW