Abstract: Abstract: Artificial Intelligence (AI) has demonstrated immense potential in the scientific domain. AI for Science (AI4S) is rapidly advancing and gaining widespread adoption, driving a comprehensive transformation in scientific research paradigms. However, the characteristics and mechanisms of AI4S in empowering scientific innovation remain unclear, and its strategic direction has yet to be systematically planned. Focusing on the 2024 Nobel Prize in Chemistry-winning projects, AlphaFold and Rosetta, this study employs a comparative case analysis to examine the distinct features and mechanisms of AI-enabled scientific research. It proposes two AI4S empowering models: "AI+" and "+AI." From the perspective of knowledge production modes, the study further analyzes the knowledge production characteristics of these two models. It identifies the emergence of "intelligence" as a fifth major actor in the "AI+" model, with knowledge production exhibiting traits of growth, independence, collaboration, and platformization. Additionally, the "AI+" and "+AI" models each have their own suitable application scenarios and frameworks. Finally, this paper offers policy recommendations, including differentiated strategies for AI+ and +AI, prioritizing small-model development, and advancing infrastructure construction. These findings contribute to both AI4S-related research and knowledge production mode theory, while also providing insights for China's development of the AI industry, exploration of AI applications, and advancement of AI models.

摘要： 人工智能（AI）在科学领域展现出巨大潜力，人工智能赋能科学研究（AI for Science, 以下简称AI4S）正快速发展与普及并推动科学研究范式全面变革，但当前AI4S赋能科研创新的特征与机制依然不明晰，AI4S布局方向仍未形成系统谋划。聚焦2024年获得诺贝尔化学奖的AlphaFold与Rosetta项目，本研究采取对比案例研究方法，分析AI赋能科学研究的不同特征与机制，提出“AI+”与“+AI”两种AI4S赋能模式。基于知识生产模式视角，本研究进一步分析两种模式的知识生产特征，提出在“AI+”模式中存在“智”第五大主体，其知识生产具有成长性、独立性、协同性、平台性特征，且“AI+”与“+AI”模式各自具有适配场景与应用模型。最后，本文提出AI+与+AI差异化战略、重视小模型开发与推动基础设施建设等政策建议。以上结论对AI4S相关研究及知识生产模式理论均有一定贡献，也对我国发展AI产业、挖掘AI场景、开发AI模型具有启示意义。