Core Viewpoint - The World Artificial Intelligence Conference (WAIC) highlighted the strategic importance of AI for Science (AI4S), marking it as one of the ten core directions with dedicated forums and discussions, indicating its transformative role in reshaping scientific foundations [3][4]. Group 1: AI for Science (AI4S) Development - AI for Science has gained significant attention, especially after AlphaFold's success in solving long-standing biological challenges, demonstrating its real-world impact [3]. - The "Starry River Enlightenment" forum, co-hosted by Fudan University and the Shanghai Institute of Intelligent Science, served as a platform for discussing the trends and innovations in AI for Science [4][5]. - The forum gathered global experts, including Turing and Nobel Prize winners, to explore collaborative innovation and industrial practices in the AI4S 2.0 era [5]. Group 2: Open Collaboration and Ecosystem Building - Fudan University emphasized the need for an open scientific ecosystem, moving beyond the "tool mindset" to a collaborative "ecological mindset" involving human scientists and AI [7]. - The "Open Science Global Academic Cooperation Initiative" was launched to address the challenges of data disparity and promote a collaborative global scientific ecosystem [31][34]. - The initiative proposes four core actions: building open infrastructure, initiating large-scale scientific projects, fostering talent development, and creating a new era of human science [34]. Group 3: Educational and Research Paradigms - The dialogue among university leaders focused on how universities will be reshaped in the AI4S 2.0 era, emphasizing the transition from a "tool mindset" to an "ecological mindset" [39][40]. - The importance of foundational research in AI was highlighted, with calls for strengthening education in mathematics and physics to cultivate top AI talent [40]. - The need for a transformation in university structures and evaluation systems was recognized to adapt to the evolving landscape of scientific intelligence [40]. Group 4: Industry and Academic Collaboration - The forum discussions revealed a consensus on the necessity for collaboration among industry, academia, and new research institutions to foster a thriving ecosystem for AI4S [44]. - Industry representatives pointed out the mismatch between AI model generation and experimental validation, advocating for automated laboratories to bridge this gap [45]. - Academic perspectives focused on enhancing model learning capabilities and addressing ethical concerns related to AI applications in sensitive fields like life sciences [47]. Group 5: Practical Applications and Ethical Governance - The "Starry River Enlightenment" platform was introduced as a comprehensive system to empower scientists by providing open data, shared models, and automated experimental capabilities [53]. - Specific applications showcased the potential of AI in various fields, including life sciences and humanities, demonstrating its broad impact [55][56]. - Ethical governance was emphasized as crucial for the sustainable development of the ecosystem, with initiatives to enhance the efficiency and professionalism of ethical reviews in research [66][68].