"追寻克孜尔壁画30年，我始终被一个问题牵引：那些被剥离带走的壁画，究竟画着什么？是'太赫兹时 域光谱技术'和AI的创新应用，让1700岁的克孜尔壁画重生。当数字复原的长卷铺展眼前，裂痕与烟渍依 旧刺痛着我。" "我问AI助手元宝，怎么让年轻人觉得太极很酷？它说，不要试图去说服年轻人我们老祖宗的东西很酷， 你要用他们的语言、审美把太极打造成一款解决他们痛点的潮流产品。" 12月12日，腾讯探元创新大会在北京首钢园举行，来自新疆维吾尔自治区龟兹研究院研究馆员赵莉、北 京邮电大学交互技术与体验系统实验室副主任陈洪等四位文博领域创新实践者，从不同维度分享了科技 助力文化遗产保护与活化的故事，引发台下专家学者共鸣。 会上，全新升级的"探元计划NextGen"正式启动，重点聚焦"AI考古"与"活化利用"两大赛道，旨在深度拓 展AI等前沿关键技术应用，助力破解考古探源与文化遗产保护与活化的前沿难题。 传统考古工作长期面临耗时长、高度依赖专家经验、数据处理效率低等现实挑战。人工智能的快速发 展，为考古学提供了前所未有的机遇。"探元计划NextGen"致力于将人工智能技术深度融入考古学研究与 实践，从文物智能复原、数据智能分 ...

Core Insights - The article discusses the introduction of Aeneas, a multimodal generative AI tool developed by DeepMind, which aids archaeologists in interpreting and restoring ancient inscriptions, significantly enhancing their research capabilities [1][9]. Group 1: Aeneas Overview - Aeneas is a multimodal generative neural network that assists historians in better interpreting, attributing, and restoring fragmented texts [1][9]. - It can analyze a vast collection of Latin inscriptions, providing context and meaning to isolated fragments, thus leading to richer conclusions about ancient history [9][10]. Group 2: Functionality and Accuracy - Aeneas can predict the dating of inscriptions within a 13-year range with a 72% accuracy rate, categorizing them into one of 62 ancient Roman provinces [9][10]. - It can repair damaged inscriptions with up to 73% accuracy for segments missing up to ten characters, and 58% accuracy when the length of the missing text is unknown [9][10]. Group 3: Historical Context and Applications - The tool is designed to handle various ancient languages and mediums, expanding its utility to connect broader historical evidence [10]. - Aeneas utilizes a large and reliable dataset, incorporating decades of historical research, to create a historical fingerprint for each inscription, allowing for contextual analysis [13]. Group 4: Case Study - Aeneas was applied to analyze the famous inscription "Res Gestae Divi Augusti," providing a probability distribution for its dating rather than a fixed date, reflecting the ongoing scholarly debate [15][17]. - The model's predictions highlight the nuances in language and historical context, offering a new quantitative approach to historical debates [15][17]. Group 5: Future Implications - The application of AI in archaeology is gaining traction, with institutions like Fudan University offering courses on AI archaeology, indicating a growing need for tools like Aeneas to sift through vast amounts of historical data [17].