Scholars at Tel Aviv University and Ariel University, in Israel, have used artificial intelligence to translate fragments of ancient cuneiform texts on stone tablets into English with what they say is a high degree of accuracy. They call the project “another major step toward the preservation and dissemination of the cultural heritage of ancient Mesopotamia.”

The scholars presented the first neural machine translation from Akkadian into English in the May issue of PNAS Nexus. Their results are “on par with those produced by an average machine translation from one modern language to another,” noted Arkeonews.

In the last 200 years, archaeologists have found hundreds of thousands of texts that tell the history of ancient Mesopotamia, most of them written in Sumerian or Akkadian, explained the authors. But most remain untranslated because of their vast quantity and the small number of experts who can read them, as well as the fact that most of the texts are fragmentary. Furthermore, cuneiform signs are polyvalent, there are many different kinds of texts, and even the names of people and places can be written as complex sentences.

“First, let me state that we believe that A.I. will not replace philological work,” said Luis Sáenz, of the Digital Pasts Lab in the Department of Land of Israel Studies and Archaeology at Ariel University, one of the authors, in an email to Artnet News. “We want to speed up the process. Our hope is that A.I. will eventually be able to help both Assyriologists and non-Assyriologists read cuneiform texts in the future.”

This is just the latest example of scientists using the newest tools to work with the oldest materials. University of Kentucky researchers developed an A.I. system to read scrolls that were incinerated when Mount Vesuvius erupted in the year 79, and archaeologists in Italy are working on a robot that uses A.I. to reconstruct ancient relics from their scattered shards.

“There are, of course, limitations to the model,” says Sáenz. “The lack of context makes ancient languages difficult to translate, since we only have fragments of texts. Fragments with only one or two lines are extremely difficult to work with for A.I. The future will require more tools to digitize data published in papers in order to keep training the model and to improve the results. Also, a user-friendly web-based platform for the public is important.”

More Trending Stories:  

The Smithsonian National Museum of African Art’s Director Has Resigned After Less Than Two Years, Citing ‘Resistance and Backlash’ 

‘We’re Not All Ikea-Loving Minimalists’: Historian and Author Michael Diaz-Griffith on the Resurgence of Young Antique Collectors 

The First Auction of Late Billionaire Heidi Horten’s Controversial Jewelry Proves Wildly Successful, Raking in $156 Million 

An Airbnb Host Got More Than They Bargained for with a Guest’s Offbeat Art Swap—and the Mystery Has Gone Viral on TikTok 

Not Patriarchal Art History, But Art ‘Herstory’: Judy Chicago on Why She Devoted Her New Show to 80 Women Artists Who Inspired Her 

An Artist Asked ChatGPT How to Make a Popular Memecoin. The Result Is ‘TurboToad,’ and People Are Betting Millions of Dollars on It 

An Elderly Man Spray-Painted a Miriam Cahn Painting at a Paris Museum After Right-Wing Attempts to Censor It Failed 

The Netflix Series ‘Transatlantic’ Dramatizes the Effort to Evacuate Artists From France During World War II. Here’s What Actually Happened in Real Life