21-year-old Luke Farritor, a computer science student at the University of Nebraska-Lincoln, has made a groundbreaking discovery by using a machine-learning algorithm to read the first-ever text from a burnt scroll found in the ancient city of Herculaneum. His breakthrough could lead to the deciphering of numerous currently unreadable ancient texts. Farritor won $40,000 in the Vesuvius Challenge competition for his achievement.
21-Year-Old Student Deciphered Ancient Herculaneum Scrolls Using AI
A groundbreaking discovery has been made by Luke Farritor, a 21-year-old computer science student at the University of Nebraska-Lincoln. He successfully read the first-ever text from a burnt scroll found in the ancient city of Herculaneum, which had been hidden since the volcanic eruption of Mount Vesuvius in AD 79. This breakthrough could potentially unlock the understanding of hundreds of currently unreadable ancient texts.
Farritor utilized a machine-learning algorithm to identify Greek letters in the charred and rolled-up papyri. By training the algorithm to detect ink using small changes in the scroll’s surface, he decoded the word “porphyras,” meaning ‘purple’ in Greek. This finding is a significant achievement as it allows scholars to see the contents of the scroll for the first time.
The Vesuvius Challenge, a larger project aiming to decode text from ancient scrolls buried by Mount Vesuvius, awarded Farritor the ‘first letters’ prize of $40,000 for his accomplishment. Historians believe that deciphering these scrolls could revolutionize our understanding of ancient history.
Brent Seales and his team, who initiated the Vesuvius Challenge, had been working on methods to virtually unwrap the scrolls using X-ray CT scans. This new technique, which Farritor utilized, can identify ink on the papyrus by detecting tiny changes in texture.
AI has been increasingly employed to study ancient texts, such as the AI tool Ithaca, which aids in dating and identifying ancient Greek inscriptions. Seales is optimistic that machine learning can help unveil the “invisible library” of physically existing but currently unreadable texts.
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