A New Chatbot Wants to Unlock the Secrets in Tattered Ancient Greek Records

Academic libraries across the globe are stuffed with hundreds of thousands of Ancient Greek papyrus fragments. Though many are so damaged that their meaning is probably lost, scholars have the ability to restore the rest by methodically filling in missing words or phrases. To accelerate that laborious task, researchers have turned to artificial intelligence.

On Wednesday, the Austrian Academy of Science will release “the world’s first advanced large language model for Ancient Greek,” developed in partnership with French AI lab Mistral and technology services firm Sail Reply. The model, Apollo, is trained on roughly 600 million historical Greek words drawn from manuscripts, papyri, and inscriptions.

The model will be freely available to academics through a chatbot interface. The ambition is to help scholars to more rapidly identify papyrus fragments relevant to their specific sub-disciplines, as well as promising new avenues of research. Where documents are tattered and torn, Apollo is built to fill in the blanks with the most statistically likely words or passages, potentially revealing hidden details about historical events and practices.

Dimitris Vlitas, partner at Sail Reply, tells WIRED that unlocking knowledge in this way “was unthinkable a year ago.”

Until now, restoring a tattered piece of papyrus has required a skilled academic to first identify the word divisions—there are no gaps in Ancient Greek writing—then accurately date the document, weigh the appropriate socio-political contexts, and consult reference materials to help choose suitable words to fill in the gaps. “There are very few people in the world who are that good at Greek history,” says Stephen Colvin, a professor of classics and historical linguistics at University College London.

Academics who find themselves bogged down in painstaking reconstruction work expect Apollo to accelerate things, allowing them to focus on the implications of historical documents, rather than figuring out what they say.