西丽湖路演社联合创投中国科创路演厅在清华大学举办了AI for Science专场活动，吸引了200余位来自政府部门、高校科研团队、创投机构、产业资本及产业服务方的代表参与1。此次活动旨在推动科研成果与创投资本、产业需求的对接转化。
本场路演展示了科学算力、AI芯片、材料智能研发、自主实验室、生物数字仿真等多个创新方向的项目1。与会者深入探讨了AI for Science作为继实验、理论、计算、数据之后的第五大科研范式1在产业化过程中面临的共性挑战，包括垂直领域专用模型准确度提升空间有限、干湿实验室协同闭环尚未形成、高质量标准化可训练数据供给不足等问题1。
不同细分领域的商业化进展存在差异1。其中制药行业的商业化进度相对领先，而材料赛道的商业化落地难度更高1。
The West Lihu Roadshow Society, in partnership with China Creation Investment and Innovation Roadshow Hall, organized a specialized AI for Science event at Tsinghua University, drawing over 200 participants including government officials, university researchers, venture capital firms, industrial investors, and industry service providers 1. The gathering featured demonstrations of breakthrough innovations spanning scientific computing power, AI chips, intelligent materials research and development, autonomous laboratories, and biological digital simulation 1.
Discussions at the event identified AI for Science as the fifth major scientific research paradigm, following experimentation, theory, computation, and data 1. Industry participants highlighted three critical shared challenges facing commercialization: the need for improved accuracy in vertical domain-specific AI models, the absence of integrated wet and dry laboratory collaboration workflows, and insufficient supply of high-quality standardized training data 1. The sector also faces divergent commercialization timelines across different segments, with the pharmaceutical industry demonstrating more advanced commercial progress while materials science tracks present steeper commercialization obstacles 1.
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