生物世界·2025-07-24 07:31Core Viewpoint - The development of the Aeneas model by Google's DeepMind aims to assist historians in analyzing and contextualizing ancient Latin inscriptions, addressing the challenges posed by incomplete texts and the vast amount of data available [3][6]. Group 1: Aeneas Model Development - The Aeneas model is a generative AI tool designed to find relationships between Roman-era Latin inscriptions and other texts, helping to determine the context of these inscriptions and predict missing parts [3][6]. - The model was trained on a merged dataset containing 176,861 inscriptions, with 5% accompanied by images, spanning from the 7th century BC to the 8th century AD [6]. Group 2: Model Functionality and Performance - Aeneas consists of three neural networks, each responsible for different tasks: repairing missing text, predicting text origins, and assessing dating [7]. - Historians found that Aeneas provided useful contextual suggestions 90% of the time, improving confidence in key tasks by 44% [7]. - The model's dating accuracy showed a margin of error of less than 13 years, compared to historians' 31 years, indicating a significant improvement in dating inscriptions [7]. Group 3: Practical Applications - Aeneas demonstrated effectiveness in analyzing altars with Latin inscriptions, identifying connections between inscriptions from the same region without prior geographical knowledge [8]. - The model successfully repaired a damaged inscription from a bronze military certificate issued by a Roman emperor, showcasing its ability to handle large datasets that are challenging for humans [10]. - Aeneas provides more logical answers based on its evidence base, contrasting with other popular AI tools that may generate random guesses [10].