国务院不久前印发的《关于深入实施"人工智能+"行动的意见》，明确提出加快实施"人工智能+"科学技 术行动。这是党中央准确把握科技发展大势作出的重要战略部署，指引我们在新一轮科研范式变革中抢 占先机。 例如，针对我国用于AI训练的数据质量良莠不齐、依赖国外数据库资源、数据标准不统一等问题，当 务之急是加快构建国家级数据平台和算力网络，促进跨平台、跨学科的优质科学数据资源安全共享与高 效应用。再如，针对多学科交叉人才短缺这一问题，则需要加强相关学科与人工智能交叉领域的复合型 人才培养。 面对新形势新挑战，广大科技工作者应积极拥抱新浪潮，探索使用人工智能手段解决重大科学问题。有 关部门也要瞄准问题症结，强化跨领域、跨部门协同攻关，让人工智能真正成为科学家们的超级助手， 助力提升科研效率和创新潜能。 （文章来源：经济日报） 近年来，人工智能驱动的科学研究在全球持续升温，展现出重塑科技创新的巨大潜力，科学研究正迈 向"人工智能+科学"的新范式。一个颇具代表性的例子就是人工智能模型阿尔法折叠2（AlphaFold2）准 确预测蛋白质结构。由于组成蛋白质多肽链的氨基酸数量极为庞大，根据已知的氨基酸序列预测蛋白质 三维结构， ...

Core Insights - The "Panshi Scientific Foundation Model" was officially launched on July 26, 2025, aiming to provide robust intelligent support for technological innovation across various fields, leveraging AI to reshape scientific research paradigms [4][11] - The model addresses challenges in the current "AI + Science" research landscape, such as data silos and insufficient reasoning capabilities, by promoting a platform-based and systematic transformation [5][11] Group 1: Model Capabilities - The "Panshi Scientific Foundation Model" is trained on specialized scientific knowledge and data, enabling deep understanding of various scientific modalities, including waves, spectra, and fields [4][7] - It features a heterogeneous mixed expert architecture, integrating proprietary models tailored for common scientific data modalities, and has achieved top performance in international datasets across mathematics, physics, chemistry, materials, and biology [7][9] Group 2: Applications and Efficiency - The model has been applied in multiple disciplines, significantly accelerating research processes, such as achieving over 10 times faster efficiency in drug target discovery in life sciences [9][10] - It supports the automation of particle physics research tasks and enhances the efficiency of high-speed train model calculations in fluid environments [9][10] Group 3: Tools and Ecosystem - The "Panshi Literature Compass" assists researchers in literature review and evaluation, processing 170 million scientific documents and reducing research time from days to minutes [8][11] - The "Panshi Tool Scheduling Platform" allows for the autonomous planning and invocation of over 300 scientific computing tools, improving research workflow efficiency [8][11] Group 4: Collaborative Initiatives - The Chinese Academy of Sciences has initiated the "Scientific Foundation Model Ecological Alliance" plan, collaborating with over 40 research institutions, universities, and enterprises to foster a new ecosystem for "AI + Science" [11]