![]() “Porphyras” is an exciting word: it means “purple” and is quite rare in ancient texts. Independently and unanimously, they annotated 13 letters, albeit with varying levels of confidence: Each square represents one review. When professor Seales showed this image to our team of papyrologists, scholars specializing in works on papyrus, they gasped: they could immediately read the word “porphyras,” despite the letters being faint.Īfter thorough technical review, we sent a newer version of his picture to the panel of papyrologists. This was his first submission: Luke’s first submission, faintly showing the word ΠΟΡΦΥΡΑϹ (porphyras). Luke then made a submission to our First Letters Prize, which required contestants to find at least 10 letters in a 4 cm2 area. Soon, these traces began to form letters and hints of actual words. Right: Resulting binary ink label.īefore long, the model was unveiling traces of crackle invisible to his own eye. Left: cracked ink visible against papyrus fiber background. He found a few dozen ink strokes - and some complete letters - that could be labeled and used as training data. With each new crackle found, the model improved, revealing more crackle in the scroll - a cycle of discovery and refinement. ![]() He saw Casey’s crackle pattern being discussed in the Discord, and began spending his evenings and late nights training a machine learning model on the crackle pattern. Luke Farritor, a college student and SpaceX summer intern working at Starbase, had heard about the Vesuvius Challenge from Dwarkesh Patel’s podcast interview with Nat. Luke Farritor’s model Īfter this discovery, several contestants looked for more crackle, but it seemed quite rare. It could be a “pi” or the bottom of a capital “eta”. ![]() Stephen Parsons had seen direct evidence of ink in detached fragments before, but not yet in the scrolls.Ĭasey was the first person in 2,000 years to find ink - and a letter - inside an unopened scroll. This was a major and surprising discovery. In early August, contestant Casey Handmer, an ex-JPL startup founder and polymath, wrote a blog post about his discovery of a “crackle pattern” that looks like ink.Ĭasey found the pattern by staring at the segmented CT scans for hours on end. Progress of mapping the scrolls, in area (cm²), from the Segment Directory spreadsheet. By July we had segmented and “virtually flattened” hundreds of cm2 of papyrus. They began mapping the 3D structure of the scroll using tools initially built by EduceLab and improved by our community. They launched an open competition March of 2023, and - alongside a $700,000 Grand Prize - awarded several smaller prizes for the development of open source tools and techniques.Įarly in the summer, a small team of annotators (the “segmentation team”) joined our effort. That success caught the eye of tech entrepreneurs Nat Friedman and Daniel Gross, who started the Vesuvius Challenge to accelerate this progress. Professor Seales’ graduate student, Stephen Parsons, worked on detecting ink from the CT-scans using machine learning models and found success with the detached fragments. Training a machine learning model on the ground truth data from the detached fragments. His team also scanned and photographed detached scroll fragments bearing visible ink, thus providing a ground truth dataset. Professor Seales and team scanning at the particle accelerator. ![]() Our story starts in 2019, when professor Brent Seales at the University of Kentucky’s EduceLab imaged Herculaneum scrolls in a particle accelerator, generating 3D CT-scans at resolutions as high as 4 µm. So how did we get here, and how do these models work? Let’s start with a little history. Congratulations to Casey, Luke, and Youssef! We’re awarding him a $10,000 First Ink Prize. His insights led directly to Luke’s discovery, as well as an improved understanding of the ink signal. These breakthroughs were both inspired by contestant Casey Handmer, who was the first person to find substantial, convincing evidence of ink within the unopened scrolls, as explained in his blog post and this video.
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