用生成神经网络对古文进行上下文化
Yannis Assael1, Thea Sommerschield2, Alison Cooley3
1Google DeepMind, London, UK. yannisassael@google.com.
Nature
|July 23, 2025
概括
一个新的生成神经网络,艾尼阿斯, 帮助历史学家对古代铭文进行背景分析. 这种人工智能工具显著改善了研究的起点,
科学领域:
- 数字人文科学
- 人工智能在历史上的作用
背景情况:
- 古代铭文提供了对历史文明的直接洞察.
- 目前用于分析铭文的数字方法仅限于字面匹配和狭窄的范围.
- 历史学家依赖于识别文本上的平行来进行上下文化,修复和归因.
研究的目的:
- 介绍一下Aeneas, 一个创新的神经网络,
- 利用人工智能检索文本和上下文并行,利用视觉输入和恢复文本.
- 推进历史文本分析任务的最新技术.
主要方法:
- 一个用于古代文本上下文化的生成神经网络Eneas的开发.
- 整合文字和视觉数据处理能力.
- 通过一项涉及历史学家的大规模研究进行评估,
主要成果:
- 历史学家发现艾尼阿斯在90%的案例中找到了相似之处,
- 艾尼阿斯的历史学家在修复和地理归因方面表现优于人类和人工智能.
- 埃尼阿斯在测年时取得了13年的准确性,与基本真相相比.
结论:
- 通过提供上下文并行并协助文本分析,Aeneas显著增强了历史研究工作流程.
- 人工智能与历史方法的整合为了解过去提供了变革性的工具.
- 埃尼阿斯展示了人工智能的潜力,通过铭文分析来推进古代文明的研究.
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