论文标题

科学发现的计算曲折

A Computational Inflection for Scientific Discovery

论文作者

Hope, Tom, Downey, Doug, Etzioni, Oren, Weld, Daniel S., Horvitz, Eric

论文摘要

我们站在科学发现轨迹中的重大变化脚下。随着社会快节奏的数字化转型的继续,人类的集体科学知识和话语也是如此。现在,我们以数字化形式读和撰写论文,并以数字方式捕获了大量的正式和非正式科学过程 - 包括论文,预印本和书籍,代码和数据集,会议演示文稿以及社交网络以及协作和交流平台的互动。过渡导致了大量信息的创建和增长(其中大部分用于公共访问)为分析和利用它的计算模型和系统打开了令人兴奋的机会。同时,数据处理能力的指数增长推动了人工智能的显着进步,包括能够从非结构化文本中学习强大表示的大型神经语言模型。科学交流的巨大变化 - 例如17世纪第一本科学杂志的出现 - 历史上已经催化了科学思想的革命。社会和计算趋势的汇合表明,计算机科学有望在科学过程本身中引发一场革命。

We stand at the foot of a significant inflection in the trajectory of scientific discovery. As society continues on its fast-paced digital transformation, so does humankind's collective scientific knowledge and discourse. We now read and write papers in digitized form, and a great deal of the formal and informal processes of science are captured digitally -- including papers, preprints and books, code and datasets, conference presentations, and interactions in social networks and collaboration and communication platforms. The transition has led to the creation and growth of a tremendous amount of information -- much of which is available for public access -- opening exciting opportunities for computational models and systems that analyze and harness it. In parallel, exponential growth in data processing power has fueled remarkable advances in artificial intelligence, including large neural language models capable of learning powerful representations from unstructured text. Dramatic changes in scientific communication -- such as the advent of the first scientific journal in the 17th century -- have historically catalyzed revolutions in scientific thought. The confluence of societal and computational trends suggests that computer science is poised to ignite a revolution in the scientific process itself.

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