DeepMind’s new AI model helps decipher, date, and locate ancient inscriptions

Machine learning techniques are providing new tools that could help archaeologists understand the past — particularly when it comes to deciphering ancient texts. The latest example is an AI model created by Alphabet-subsidiary DeepMind that helps not only restore text that is missing from ancient Greek inscriptions but offers suggestions for when the text was written (within a 30-year period) and its possible geographic origins.

“Inscriptions are really important because they are direct sources of evidence … written directly by ancient people themselves,” Thea Sommerschield, a historian and machine learning expert who helped created the model, told journalists in a press briefing.

Due to their age, these texts are often damaged, making restoration a rewarding challenge. And because they are often inscribed on inorganic material like stone or metal, it means methods like radiocarbon dating can’t be used to find out when they were written. “To solve these tasks, epigraphers look for textual and contextual parallels in similar inscriptions,” said Sommerschield, who was co-lead on the work alongside DeepMind staff research scientist Yannis Assael. “However, it’s really difficult for a human to harness all existing, relevant data and to discover underlying patterns.”

That’s where machine learning can help.

Ancient Greek inscriptions are often fragmented. The software Ithaca can suggest what letters are missing.
Image: DeepMind

The new software, named Ithaca, is trained on a dataset of some 78,608 ancient Greek inscriptions, each of which is labeled with metadata describing where and when it was written (to the best of historians’ knowledge). Like all machine learning systems, Ithaca looks for patterns in this information, encoding this information in complex mathematical models, and uses these inferences to suggest text, date, and origins.

In a paper published in Nature that describes Ithaca, the scientists who created the model say it is 62 percent accurate when restoring letters in damaged texts. It can attribute an inscription’s geographic origins to one of 84 regions of the ancient world with 71 percent accuracy and can date a text to within, on average, 30 years of its known year of writing.

These are promising statistics, but it’s important to remember that Ithaca is not capable of operating independently of human expertise. Its suggestions are ultimately based on data collected by traditional archaeological methods, and its creators are positioning it as simply another tool in a wider set of forensic methods, rather than a fully-automated AI historian. “Ithaca was designed as a complementary tool to aid historians,” said Sommerschield.

Ithaca is the first model to geographical and chronological attribution with textual restoration.
Image: DeepMind

Eleanor Dickey, a professor of classics from the University of Reading who specializes in ancient Greek and Latin sociolinguists, told The Verge that Ithaca was an “exciting development that may improve our knowledge of the ancient world.” But, she added that a 62 percent accuracy for restoring lost text was not reassuringly high — “when people rely on it they will need to keep in mind that it is wrong about one third of the time” — and that she was not sure how the software would fit into existing academic methodologies.

For example, DeepMind highlighted tests that showed the model helped improve the accuracy of historians restoring missing text in ancient inscriptions from 25 percent to 72 percent. But Dickey notes that those being tested were students, not professional epigraphers. She says that AI models may be broadly accessible, but that doesn’t mean they can or should replace the small cadre of specialized academics who decipher texts.

“It is not yet clear to what extent use of this tool by genuinely qualified editors would result in an improvement in the editions generally available — but it will be interesting to find out,” said Dickey. She added that she was looking for to trying the Ithaca model out for herself. The software, along with its open-source code, is available online for anyone to test.

Ithaca and its predecessor (named Pythia and released in 2019) have already been used to help recent archaeological debates — including helping date inscriptions discovered in the Acropolis of Athens. However, the true potential of the software has yet to be seen.

Sommerschield stresses that the real value of Ithaca may be in its flexibility. Although it was trained on ancient Greek inscriptions, it could be easily configured to work with other ancient scripts. “Ithaca’s architecture makes it really applicable to any ancient language, not just Latin, but Mayan, cuneiform; really any written medium — papyri, manuscripts,” she said. “There’s a lot of opportunities.”

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Diablo II: Resurrected will support your ancient original game saves

Blizzard has just dropped a somewhat surprising detail about its recently announced Diablo II: Resurrected remastered game: you’ll be able to import your decades’ old game saves from the original title, allowing you to pick up where you left off. The original Diablo II game was released in June 2000 and now has the honor of being a cult classic.

As you’d expect from a remastered title, Diablo II: Resurrected brings support for the latest consoles, as well as PC, with 4K, updated graphics, and more. The game is expected to be released by December 2021, but can be preordered now for $39.99 USD (Standard) and $59.99 USD (Prime Evil Collection).

Ultimately, fans are promised the game they fell in love with 20 years ago, but with the polish and tweaks necessary to make it an even better version of an already great game. This effort was recently detailed by the title’s game producer and game designer Matthew Cederquist and Andre Abrahamian in an interview with IGN Middle East.

As expected, players will be able to cross-save the game so that they can enjoy the experience across all of their supported hardware — however, cross-play won’t be a thing, at least not at launch. As the final question in the interview, the duo was asked whether players will be able to import their original game save files.

“Yes!” Matthew said, “Yes, keep those!” He went on to explain that the team behind the remastered title wondered whether the original game save files would work, ‘and we kind of shoved it in and it worked!’ The support covers the local single-player original game save files.

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How a designer used AI and Photoshop to bring ancient Roman emperors back to life

Machine learning is a fantastic tool for renovating old photos and videos. So much so that it can even bring ancient statues to life, transforming the chipped stone busts of long-dead Roman emperors into photorealistic faces you could imagine walking past on the street.

The portraits are the creation of designer Daniel Voshart, who describes the series as a quarantine project that got a bit out of hand. Primarily a VR specialist in the film industry, Voshart’s work projects got put on hold because of COVID-19, and so he started exploring a hobby of his: colorizing old statues. Looking for suitable material to transform, he began working his way through Roman emperors. He finished his initial depictions of the first 54 emperors in July, but this week, he released updated portraits and new posters for sale.

Voshart told The Verge that he’d originally made 300 posters in his first batch, hoping they’d sell in a year. Instead, they were gone in three weeks, and his work has spread far and wide since. “I knew Roman history was popular and there was a built-in audience,” says Voshart. “But it was still a bit of a surprise to see it get picked up in the way that it did.”

To create his portraits, Voshart uses a combination of different software and sources. The main tool is an online program named ArtBreeder, which uses a machine learning method known as a generative adversarial network (or GAN) to manipulate portraits and landscapes. If you browse the ArtBreeder site, you can see a range of faces in different styles, each of which can be adjusted using sliders like a video game character creation screen.

Voshart fed ArtBreeder images of emperors he collected from statues, coins, and paintings, and then tweaked the portraits manually based on historical descriptions, feeding them back to the GAN. “I would do work in Photoshop, load it into ArtBreeder, tweak it, bring it back into Photoshop, then rework it,” he says. “That resulted in the best photorealistic quality, and avoided falling down the path into the uncanny valley.”

Voshart says his aim wasn’t to simply copy the statues in flesh but to create portraits that looked convincing in their own right, each of which takes a day to design. “What I’m doing is an artistic interpretation of an artistic interpretation,” he says.

To help, he says he sometimes fed high-res images of celebrities into the GAN to heighten the realism. There’s a touch of Daniel Craig in his Augustus, for example, while to create the portrait of Maximinus Thrax he fed in images of the wrestler André the Giant. The reason for this, Voshart explains, is that Thrax is thought to have had a pituitary gland disorder in his youth, giving him a lantern jaw and mountainous frame. André the Giant (real name André René Roussimoff) was diagnosed with the same disorder, so Voshart wanted to borrow the wrestler’s features to thicken Thrax’s jaw and brow. The process, as he describes it, is almost alchemical, relying on a careful mix of inputs to create the finished product.

A print, now available to buy, of all of Voshart’s photorealistic Roman emperors.
Image by Daniel Voshart

Perhaps surprisingly, though, Voshart says he wasn’t really that interested in Roman history prior to starting this project. Digging into the lives of the emperors in order to create his portraits has changed his mind, however. He’d previously dismissed the idea of visiting Rome because he thought it was a “tourist trap,” but now says “there are specific museums I want to hit up.”

What’s more, his work is already enticing academics, who have praised the portraits for giving the emperors new depth and realism. Voshart says he chats with a group of history professors and PhDs who’ve given him guidance on certain figures. Selecting skin tone is one area where there’s lots of dispute, he says, particularly with emperors like Septimius Severus, who’s thought to have had Phoenician or perhaps Berber ancestors.

Voshart notes that, in the case of Severus, he’s the only Roman emperor for whom we have a surviving contemporary painting, the Severan Tondo, which he says influenced the darker skin tones he used in his depiction. “The painting is like, I mean it depends on who you ask, but I see a dark skinned North African person,” says Voshart. “I’m very much introducing my own sort of biases of faces I’ve known or have met. But that’s what I read into it.”

As a sort of thank you to his advisers, Voshart has even used a picture of one USC assistant professor who looks quite a bit like the emperor Numerian to create the ancient ruler’s portrait. And who knows, perhaps this rendition of Numerian will be one that survives down the years. It’ll be yet another artistic depiction for future historians to argue about.

You can read more about Voshart’s work here, as well as order prints of the emperors.

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