Core Insights - The article discusses the emergence of key infrastructure for AI for Science (AI4S), indicating that the time for scalable, agent-driven scientific research has matured [3]. Group 1: Event Overview - A seminar titled "Agentic Science at Scale" was held on January 29, co-hosted by Shanghai Jiao Tong University and the Shanghai Algorithm Innovation Research Institute, where core achievements like the Innovator model and SciMaster research agent were presented [3][4]. - The seminar featured a keynote speech by Academician E Wei Nan, who outlined the foundational capabilities and implementation paths for the era of intelligent and scalable scientific research [3]. Group 2: Key Developments - The SciMaster research agent, presented by Associate Professor Chen Siheng, aims to achieve a closed-loop process in scientific research across all disciplines, providing an "autonomous driving" experience with capabilities that can match the work output of a seasoned theoretical physics PhD in just 6 hours [4]. - The Innovator model, introduced by Assistant Professor Zhang Linfeng, achieves three goals: multi-modal scientific perception, scientific reasoning, and scientific tool invocation, supporting over 20 scientific modalities and demonstrating superior general visual understanding capabilities [4]. Group 3: Strategic Collaborations - Strategic cooperation agreements were signed between Shanghai Sairande Intelligent Technology Co., Ltd. and other companies, focusing on research computing power supply and data value mining [4].

Group 1 - The key infrastructure for AI for Science (AI4S) is gradually taking shape, marking the maturity of large-scale, agent-driven scientific research [1][3] - The "Agentic Science at Scale" era has officially begun, as stated by the chief advisor of the Shanghai Jiao Tong University AI Institute during the opening report [3] - The conference introduced core achievements such as the Innovator scientific base model and the SciMaster research agent, aimed at bridging the last mile of intelligent and scalable scientific research through industry-academia-research strategic agreements [1][3] Group 2 - The SciMaster research agent is designed to achieve a closed-loop process in scientific research across all disciplines, providing an "autonomous driving" experience that can match the output of a senior theoretical physics PhD in just 6 hours of operation [3][4] - The Innovator base model achieves three goals: multi-modal scientific perception, scientific reasoning, and scientific tool invocation, supporting over 20 scientific modalities and demonstrating superior general visual understanding capabilities [4] - Strategic cooperation agreements were signed between Shanghai Sailande Intelligent Technology Co., Ltd. and other companies to collaborate on research computing power supply and data value mining [4]