人工智能技术如何赋能学科建设？人工智能技术给创新人才培养带来哪些启示？智通财经特推出"大学 2025"专题，以深入探讨人工智能时代的大学之变。 日前，中国工程院院士、福州大学校长吴明红在接受智通财经专访时表示，人工智能对于高等教育，不 是一场需要抵御的风暴，而是一股可以借力的"东风"。 在人工智能与人形机器人的一骑绝尘中，中国大学迎来2025。 2025年，注定要成为变革的年份。是以战略敏捷赢得战略主动，还是在延误中错失转型机遇，中国大学 踏上征途。 中国工程院院士、福州大学校长吴明红。本文图片均由福州大学提供，海报摄影：苏瑛荃，海报设计： 祝碧晨 近日，中国工程院院士、福州大学校长吴明红在接受智通财经专访时阐述了学校推动人工智能赋能高等 教育实现提质增效的具体路径。自执掌福州大学以来，她将科研洞察与战略视野深度融入治校实践，积 极推动学校在战略布局与学科交叉、人才培养模式创新、科技服务社会等方面实施系统性改革。 面对社会上"AI将取代某些职业"的普遍担忧，吴明红指出，"替代"只是表象，"重塑"才是本质。她认 为，AI并非简单的岗位"取代者"，而是职业生态的"重启键"。在人才培养方面，她认为："培养AI人 才 ...

Core Insights - The integration of artificial intelligence (AI) is driving rapid advancements in scientific research, becoming a consensus in the scientific community [1][3] - The Chinese government has outlined six key actions to accelerate the implementation of "AI+" in science and technology, highlighting the importance of AI in various fields such as life sciences, mathematics, and materials science [1][4] Group 1: AI's Role in Scientific Research - AI helps researchers overcome cognitive limitations, formulate better questions, and identify valuable research directions [1][3] - AI optimizes existing research tools and can autonomously create new tools or innovative combinations [1][3] - AI enables researchers to comprehensively examine research subjects, uncovering overlooked potential connections [1][3] Group 2: Challenges and Opportunities - The complexity of scientific discovery has increased, making significant breakthroughs more challenging, often limited by researchers' cognitive levels and knowledge dissemination [2] - The transition from serendipitous discoveries to systematic ones is a critical issue that AI-driven research must address [2] - The emergence of large models in AI has improved generalization capabilities but has also highlighted the need for specialized depth, making "integration of general and specialized knowledge" essential for scientific discovery [2] Group 3: Practical Applications and Innovations - AI can generate cross-disciplinary ideas, assess the value of research hypotheses, and enhance cognitive levels for better scientific questioning [3] - The Shanghai AI Laboratory has developed and open-sourced the "Shusheng" multimodal scientific model, which integrates various scientific data types and has shown promising results in quantum computing and drug development [3] - The platform based on the "Shusheng" model has made advancements in quantum computing, drug research, and polymer chemistry [3] Group 4: Future Implications - AI is expected to play a crucial role in technological innovation and will serve as a significant engine for breakthroughs across disciplines and fields [4] - Accelerating the exploration of AI-driven research paradigms and building application-oriented scientific models will enhance AI's role in achieving high-level scientific breakthroughs [4]

Core Insights - The article highlights the launch of the Intern-S1 multimodal model by Shanghai AI Laboratory, which is positioned as a leading open-source model in the field of scientific research, showcasing significant advancements in AI for science [5][12][17]. Group 1: Model Capabilities - Intern-S1 is recognized for its superior performance in scientific reasoning tasks, outperforming leading closed-source models like Grok-4, particularly in fields such as chemistry, materials science, and biology [12][17]. - The model integrates a 235 billion parameter MoE language model and a 6 billion vision encoder, trained on 5 trillion tokens, with over 2.5 trillion tokens specifically from scientific domains [25][21]. - Intern-S1 demonstrates a 70% improvement in compression rates for chemical formulas compared to previous models, indicating enhanced efficiency in processing complex scientific data [26]. Group 2: Technological Innovations - The model employs a dynamic tokenizer and temporal signal encoder to effectively handle various complex scientific modalities, addressing challenges posed by data heterogeneity and semantic understanding [26]. - Intern-S1's training costs for reinforcement learning have been reduced by tenfold due to collaborative breakthroughs in system and algorithm optimization [30]. - The model's architecture allows for a unique "cross-modal scientific analysis engine," enabling it to interpret complex scientific data such as chemical structures and seismic signals accurately [16][17]. Group 3: Open Source and Community Engagement - Since its initial release in 2023, the "ShuSheng" model family has been continuously upgraded and expanded, fostering an active open-source community with participation from hundreds of thousands of developers [32][33]. - The Shanghai AI Laboratory has launched a comprehensive open-source toolchain that includes frameworks for data processing, pre-training, fine-tuning, deployment, and evaluation, aimed at lowering barriers for research and application [32]. - The Intern-Discovery platform, based on Intern-S1, has been introduced to enhance collaboration among researchers, tools, and research subjects, promoting a new phase of scientific discovery [6][33].

Core Insights - DeepSeek has sparked widespread discussions across various industries regarding the "AI+" movement since the beginning of this year [1] - Digital China (000034) reported a revenue of 29.65 billion yuan from its cloud services and software business, driven by AI, marking an 18.75% year-on-year increase [2] - The overall revenue for Digital China in 2024 reached 128.166 billion yuan, a 7.14% increase, achieving a five-year high [2] Financial Performance - Digital China's net profit decreased by 35.57% to 777 million yuan due to asset impairment related to the International Innovation Center (IIC) [3] - Excluding the negative impact from IIC, the net profit was 1.305 billion yuan, showing positive growth [3] - Revenue from traditional IT distribution and value-added services was 124.451 billion yuan, up 6.84% year-on-year [4] AI Strategy and Developments - AI has become the core of Digital China's cloud integration strategy, with significant investments in AI capabilities [4] - The company launched the Shenzhou KunTai AI-native empowerment platform, reinforcing its position in the AI application sector [5] - Digital China is focusing on process re-engineering and optimization through AI to drive continuous innovation and breakthroughs for enterprises [2][6] Market Trends and Future Outlook - The current phase of AI application is described as the "beginning," with many enterprises yet to fully leverage AI's potential [6] - The integration of AI into business processes is expected to redefine core competitiveness, transitioning from traditional static operations to dynamic systems centered around intelligent agents [6][7] - Future AI applications for enterprises will likely involve heterogeneous computing and the integration of various models, supported by extensive internal data [7]