Core Viewpoint - The first "Fosun Cup" AI+ Entrepreneurship and Innovation Competition has been launched, aiming to integrate cutting-edge technology with industry applications, leveraging Fosun's extensive resources and global industry scenarios [1][10]. Group 1: Competition Overview - The competition is supported by Fosun's global investment institution, Fosun Ruijing Capital, which will provide investments ranging from 5 million to 50 million yuan for the top three teams [3][11]. - Winning teams will also gain priority access to over 200 industry application scenarios, including AI applications in finance, healthcare, and intelligent manufacturing [3][11]. - The competition includes cash prizes of 100,000 yuan or equivalent resources for the top teams, along with direct recruitment opportunities for outstanding teams [4][11]. Group 2: Recruitment Tracks - The competition is recruiting AI pioneers across various tracks, including AI+Finance, AI+Healthcare, AI+Marketing, AI for Science (AI4S), and AI+Intelligent Agents [4][11]. - Each track focuses on specific applications of AI, such as financial data processing, drug development, and intelligent marketing solutions [4][11]. Group 3: Competition Schedule - The project recruitment phase runs until June 15, 2025, followed by a selection process to identify over 20 enterprises for the initial round [6][7]. - The initial round will take place from June 15 to June 30, 2025, where 20+ enterprises will compete for a spot in the finals [7]. - The final competition is scheduled for July 2025, where experts and executives will evaluate the projects through presentations [8]. Group 4: Fosun's Strategic Focus - Fosun emphasizes technology innovation as a core strategic pillar, building a global innovation system that integrates independent research, investment incubation, and ecological cooperation [10][11]. - The company has made significant investments in AI and robotics, with a focus on enhancing efficiency in drug development, medical imaging, and precision medicine [10][12]. - Fosun's subsidiaries, including Fosun Pharma and Fosun Wealth Holdings, are actively integrating AI into their operations to improve decision-making, operational efficiency, and market insights [12][14].

在数字化浪潮席卷全球的今天， 人工智能（AI）正以其独特的魅力和强大的潜力，成为推动社 会进步和经济发展的新引擎。 未可知人工智能研究院，作为AI领域的先行者和探索者，一直致 力于将最前沿的AI技术和理念，转化为实际应用，以促进各行各业的创新与发展。 近日， 未可知人工智能研究院副院长张孜铭，受邀为四川省天府新区的领导干部们进行了一场 主题为"人工智能+与新质生产力——AI4S及AIGC领域的发展展望"的政务培训。 此次培训， 不仅是对AI技术在政务领域应用的一次深入探讨，更是对如何利用AI提升新质生产力的一次全 面展望。 AI 赋能政务，提升行政效 率 在培训中，张孜铭副院长首先介绍了 AI技术在政务领域的应用现状和未来趋势 。他指出，AI 技术可以通过数据分析、智能决策支持等方式，极大地提高政府决策的科学性和行政效率。同 时， AI在公共服务、城市管理、环境保护等方面的应用，也能有效提升政府服务的质量和水 平。 张副院长通过丰富的案例和详实的数据，展示了 AI技术在政务领域的广泛应用，如智能客服、 自动化办公、智能监管等。这些应用不仅提高了政府工作的效率，也为公众提供了更加便捷和 高效的服务。 新质生产力 ...

"分子宇宙"的无穷潜能正等待电池产业开掘。 北京时间4 月 29 日 晚 11 时（ 美东时间 4 月 29 日中午 11 时） ， SES AI 将公开全球首个电池领域专用 " 分子宇宙 " （ Molecular Universe ， MU-0 ），并进行公开演示。 " 分子宇宙 " 是 SES AI 推出的一款电池领域 AI4S 解决方案，涵盖 10 的 11 次方个可用于电池的小分子，并电池专用的大语言模型驱动 训练而成的导航系统，让全球顶尖电池科学家的专业知识 " 触手可及 " 。 SES AI 表示， " 分子宇宙 " 可理解为一个专用于电池材料开发的 " 导航地图 " 或 " 参考词典 " 。通过 " 分子宇宙 " 软件，用户可精准 地筛选出所需材料，打开电池材料创新想象空间。 对于电池产业链企业而言，"分子宇宙"的现实价值在于加速或替代R&D，除了现阶段查询未知分子的功能，未来"分子宇宙"还将延伸到到材 料配方、电芯设计、电池测试等多个环节，实现电池开发全流程的加速。 具体而言， " 分子宇宙 " 软件具备三大方面的优势。 首先是庞大且持续扩展的数据库 —— 分子图谱。当前版本（ MU-0 ） ...

Core Insights - AI4S represents the fifth paradigm of scientific research, integrating artificial intelligence into the entire research process to create a smart closed-loop of hypothesis generation, experimental validation, and theoretical iteration [2] - The fourfold value of AI4S includes accelerating scientific discovery, breaking traditional method limitations, reducing research costs and barriers, and driving interdisciplinary innovation [2] Industry Overview - The new materials research sector faces challenges such as complex systems, vast parameter spaces, and unclear structure-activity relationships, which AI4S can address through unified data modeling, cross-scale simulation, and autonomous experimental platforms [3] - The emergence of high-quality material data and advancements in deep learning technology have led multiple companies to adopt AI4S for new materials development [3] Company Developments - Zhite New Materials is collaborating with Quantum Technology Yangtze River Delta Innovation Center and Micron Era Digital Technology to promote the application of AI and quantum technology in new materials [4] - The company has signed a memorandum of cooperation with the University of Science and Technology of China to establish an AI4S innovation platform and develop high-performance sunscreen and heat-insulating materials [4]

Core Insights - The article emphasizes the integration of AI technology in the battery industry, highlighting its role as a core engine for breakthroughs in next-generation battery technologies [2][3][4]. Group 1: AI Integration in Battery Technology - AI is becoming essential for addressing the four core challenges in solid-state battery research, necessitating a shift to a new paradigm of AI-driven processes [2]. - The introduction of AI in the lithium battery supply chain dates back to 2019, with companies like Honeycomb Energy and CATL leading the way in AI-enhanced manufacturing [2]. - CATL's "extreme manufacturing" approach has significantly improved its profit margins, with a sales gross margin of 28.19% in the first three quarters of 2024, well above the industry average of approximately 18% [2]. Group 2: Strategic Collaborations - CATL's vision extends beyond being a battery company to becoming an energy intelligence operating system, as indicated by internal communications [3]. - A strategic partnership between Baidu and CATL aims to leverage AI capabilities for the development of autonomous vehicle products and services [3]. Group 3: AI4S Paradigm in Battery Innovation - The AI4S (AI for Science) paradigm is gaining traction in battery innovation, focusing on the integration of models, data, and computational power in battery cell design and material research [5]. - The Uni-Mol model, developed by a team from the Chinese Academy of Sciences, exemplifies the use of AI in molecular data integration for battery research [6]. Group 4: Performance Enhancements and Innovations - AI has enabled significant advancements in battery materials, such as the design of lithium carrier molecules that can rejuvenate old batteries, enhancing their lifespan [7]. - The introduction of AI-enhanced battery design is expected to improve design efficiency by 2-5 times by 2025 [8]. Group 5: AI-Driven Manufacturing Efficiency - Tesla's Texas Gigafactory showcases the effectiveness of AI in achieving manufacturing efficiency through a feedback loop of data optimization [10]. - CATL's "lighthouse factory" has achieved a 320% increase in production capacity and a 33% reduction in manufacturing costs through AI integration [11]. Group 6: Safety and Economic Benefits of AI - AI applications in battery management systems (BMS) have shown significant improvements in safety and efficiency, with Huawei's AI BMS system providing real-time safety alerts and health assessments [13]. - The collaboration between State Grid and Huawei aims to enhance the economic viability of energy storage through AI-driven coordination of distributed energy resources [15]. Group 7: Challenges in Data and Energy Consumption - The rapid accumulation of battery data raises concerns about data ownership and compliance, especially as data is recognized as a key production factor [16]. - The energy consumption of large AI models poses a challenge, with reports indicating that training models like GPT-4 consumes energy equivalent to a small power plant's annual output [16]. Group 8: Future Opportunities - The convergence of battery technology and AI presents new opportunities for redefining the relationship between energy and intelligence, potentially leading to innovative solutions in both fields [17].