Machine Learning Unlocks Ancient Scrolls

Unlocking the Secrets of Lost Ancient Texts: Revealing Insights from Buried Scrolls

By Sunil Sonkar 2 Min Read
2 Min Read
Machine Learning Unlocks Ancient Scrolls

What the lost ancient texts would have revealed? What more we would have understood about our ancestors from the ancient scrolls? These are some haunting questions and researchers have always tried to decipher information from the past. Now, there is a thrilling breakthrough. A team of experts has unveiled a method to reveal lost ancient texts hidden within carbonized papyrus scrolls. The scrolls from the ancient Roman town of Herculaneum remained dormant for centuries. These were buried beneath layers of ash from the catastrophic eruption of Mount Vesuvius in 79 CE.

Machine learning and non-invasive technology have taken an advanced step to help researchers to extract 15 columns of Greek text from these ancient relics. The achievement sheds light on the rich literary heritage of Herculaneum. The achievement simultaneously represents a significant leap forward in the field of manuscript studies.

The uncovering process of hidden treasures started with the Vesuvius Challenge. It was a collaborative effort led by computer scientist Brent Seales and technology investors Nat Friedman and Daniel Gross. Their challenge was to unlock the secrets of the past.

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The researchers used advanced imaging techniques and included high-resolution X-ray computed tomography (CT) scans for the project. It was a process of trial and error and they gradually pieced together fragments of text. Their efforts finally revealed some tantalizing glimpses into the world of ancient Greek literature.

Even though the technology helps in deciphering, the true work of interpretation still lies in the hands of human scholars. Papyrologists will now take up the work to analyze as well as make sense of the recovered texts.

Hundreds of scrolls are waiting for examination. Researchers are facing logistical hurdles as well as technical limitations. Access to specialized equipment still remains a bottleneck in the process.

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