Enter Enoch The authors of this latest paper wanted to find a better means than paleography alone for determining the chronology of the scrolls, with an eye toward reconstructing the evolution of ideas. They thought that given the small data set in the case of the scrolls, it was wisest not to rely on a pre-trained model and instead "let the available data speak." By combining writing styles with carbon-14 dates of manuscripts using artificial intelligence, the date-prediction model Enoch is able to produce an accurate date for the manuscript. By combining writing styles with carbon-14 dates of manuscripts using artificial intelligence, the date-prediction model Enoch is able to produce an accurate date for the manuscript. University of Groningen/CC BY-SA Mladen Popovic and Maruf Dhali working with Enoch to date a manuscript from the Dead Sea Scrolls. By combining writing styles with carbon-14 dates of manuscripts using artificial intelligence, the date-prediction model Enoch is able to produce an accurate date for the manuscript. University of Groningen/CC BY-SA The development of Enoch grew out of the team's earlier deep neural network for ferreting out handwritten ink-trace patterns in digitized manuscripts, involving micro-level geometric shape analysis. "Enoch emphasizes shared characteristics and similarity matching between trained and test manuscripts, where traditional paleography focuses on subtle differences that are assumed to be indicative for style development," the authors wrote. "Combining dissimilarity matching and adaptive reinforcement learning can uncover hidden patterns." They tested Enoch by having paleographic experts evaluate the AI program's age estimate for several scrolls. The results: About 79 percent of Enoch's estimates were deemed "realistic," while its age estimates for the remaining 21 percent were either too young, too old, or just indecisive. This new model revealed that many of the Dead Sea Scrolls are older than previous estimates...
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