反思科学领域的人工智能:从数据驱动到以数据为中心的框架演变

M. Maskey
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摘要

人工智能(AI)的快速发展已经在包括科学领域在内的众多学科中找到了应用。然而,以模型为中心的人工智能往往忽视了数据所起的关键作用,从而限制了其在科学研究中的有效性。本文提倡过渡到以数据为中心的观点,特别是在应用于科学进步的人工智能框架内。本文概述了以模型为中心和以数据为中心的人工智能的对比哲学,强调了后者对数据战略的承诺。它探讨了一系列支持以数据为中心的框架的技术。此外,本文概述了人工智能技术的关键里程碑,以数据为中心的人工智能的重要性和不断变化的作用,以及这一新兴领域的研究现状。
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Rethinking AI for Science: An Evolution From Data‐Driven to Data‐Centric Framework
The rapid advancements in Artificial Intelligence (AI) have found applications across a multitude of disciplines, including the scientific domain. Yet, the dominant focus on model‐centric AI often overlooks the critical role that data plays, thereby limiting its effectiveness in scientific investigations. This paper advocates for a transition to a data‐centric viewpoint, especially within the framework of AI applied to scientific advancements. The paper outlines the contrasting philosophies of model‐centric and data‐centric AI, highlighting the latter's commitment to data strategies. It explores a range of techniques that bolster the data‐centric framework. Furthermore, the paper presents an overview of key milestones in AI technology, the significance and the changing role of data‐centric AI, and the current state of research in this emerging field.
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