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].

Core Insights - The World Artificial Intelligence Conference in Shanghai highlighted the launch of the "Xinghe Qizhi Scientific Intelligence Open Platform" and the "Early Chinese Civilization Multimodal Model," showcasing advancements in scientific intelligence and AI integration [1][2]. Group 1: Scientific Intelligence 2.0 - The transition to Scientific Intelligence 2.0 emphasizes a scientist-centric approach, moving from AI empowering science to a model where scientists lead the integration of AI in research [1][2]. - The "Xinghe Qizhi" platform serves as a bridge connecting scientists with AI, facilitating their participation in scientific advancements [2]. Group 2: Platform Features - The platform offers a comprehensive solution encompassing data, models, computing power, experimental validation, and collaborative research communities, aggregating over 40,000 datasets totaling 12PB of high-value scientific data [2]. - It features a "Universal Model Warehouse" with over 200 advanced models, significantly lowering the barriers for scientists to utilize AI [2]. Group 3: Computational Efficiency - The platform's intelligent computing system optimizes the integration of GPU and CPU resources, enhancing computational efficiency and providing acceleration of several times to up to a thousand times for specific research scenarios [2]. Group 4: Data Ecosystem and Collaboration - Utilizing blockchain technology, the platform establishes a trusted scientific data ecosystem, addressing data ownership and contribution calculation issues, and incentivizing data sharing through a points system [4]. - The platform aims to integrate dry and wet experiments, facilitating seamless connections between AI simulations and real-world experiments, promoting collaboration among scientists, laboratories, and enterprises [4]. Group 5: Cultural and Historical Research - The "Early Chinese Civilization Multimodal Model" is the first AI model focused on early Chinese civilization, developed collaboratively by Fudan University and other institutions, integrating vast historical materials [4]. - This model incorporates humanities research methodologies, enabling comprehensive analysis and traceable evidence for complex and controversial questions, serving as a powerful tool for researchers [4][5]. Group 6: Vision for the Future - The conference illustrated Shanghai's unique advantages in combining top-tier university resources with AI engineering capabilities to tackle significant scientific and cultural challenges [7]. - The ongoing development of scientific intelligence aims to create inclusive and collaborative global scientific knowledge ecosystems, making scientific exploration accessible to a broader audience [7].

Core Insights - The WAIC2025 Star River Intelligent Open Cooperation Forum was held, focusing on building an open and collaborative scientific intelligence ecosystem [1] - Multiple innovative achievements were announced, including the Early Chinese Civilization Multimodal Large Model and the Global Academic Cooperation Initiative [1][3] Group 1: Early Chinese Civilization Multimodal Large Model - The Early Chinese Civilization Multimodal Large Model was officially released, developed by Fudan University, Shanghai Intelligent Research Institute, and Shanghai Chuangzhi Academy [3] - The model encompasses 100TB of specialized corpus, SFT data, and evaluation sets, pioneering cross-modal intelligent alignment of civilization spatiotemporal data [3] - It supports the Chinese Civilization AI Agent platform, enabling multi-step reasoning and complex task planning, benefiting education, research, and cultural industries [3] Group 2: Global Academic Cooperation Initiative - A global initiative was launched by top international scientists, including Nobel Prize winners, aiming to break the "data divide" and ensure AI benefits reach every corner of the globe [3] - The initiative outlines four core objectives: building open-source scientific infrastructure, initiating multinational interdisciplinary scientific programs, cultivating international scientific talent, and establishing a fair value-sharing mechanism [3][4] Group 3: Star River Intelligent Open Platform - The Star River Intelligent Open Platform was launched, designed to accelerate scientific discovery and provide comprehensive infrastructure for scientists and AI engineers [6] - It aims to enhance cross-disciplinary collaboration and address key scientific challenges, significantly speeding up scientific discoveries [6] - The platform includes the "Guanxin" large model, which formalizes complex clinical diagnosis processes into a multi-agent collaborative system for cardiovascular specialties [6] Group 4: Ethical Review AI Agent "Yijian" - The ethical review AI agent "Yijian" was introduced, capable of automatic rule review and risk labeling, enhancing review efficiency and compliance [7] - It has been trialed at Fudan University and its affiliated Zhongshan Hospital, ensuring data security and supporting the generation of review reports [7]