董事会认为，上海交大海南研究院在海洋科技、机器人及人工智能等领域拥有优质的教育资源、科研团 队及技术核心竞争能力，创新奇智在水下特种机器人及人工智能等领域拥有成熟的市场渠道、实践资源 及技术应用场景。双方建立战略合作关系，有利于深化产学研融合，在"发挥优势、整合资源、校企联 合、互利共赢"的塬则上，促进实现产学研一体，共享资源，共同融合技术、推动科技成果产业化。 创新奇智(02121)发布公告，于2026年1月28日，公司与上海交通大学海南研究院(上海交通大学三亚崖州 湾深海科技研究院)(上海交大海南研究院)签署战略合作协议。 根据战略合作协议，公司与上海交大海南研究院将共同努力推进技术、项目等方面的合作，包括海洋技 术装备研发，即依托上海交大海南研究院在深海科技、海洋装备及海上试验技术等领域的核心科研能 力，以及公司在人工智能赋能机器人的产业经验和先进的工业大模型技术，围绕水下智能作业装备、水 下多轴机械臂、水下目标识别追踪、空-海-潜一体化无人装备、海洋环境感知、海洋装备结构设计优化 等领域开展深入合作，未来共建智能海洋技术装备研究领域校企联合实验室;双方还将进行人才培养合 作、成果转化合作及资源共享与交 ...

（来源：市场星报） 星报讯 记者获悉，为深入贯彻落实国家关于人工智能赋能新型工业化的战略部署，1月28日上午，省工 业和信息化厅举办"安徽省首批工业大模型发布会暨推广应用启动会"，会上正式发布了涵盖研发设计、 生产制造、质量检测、故障预测等多个环节的首批23个工业大模型。 会议指出，工业大模型是推动制造业智能化转型、构建现代化产业体系的重要抓手。安徽紧抓人工智能 与实体经济深度融合的战略机遇，系统推进工业大模型技术攻关、场景拓展与生态构建，取得了一系列 阶段性成果。首批23个工业大模型的发布，是安徽贯彻落实国家人工智能发展战略、推动制造业高质量 发展的重要举措。下一步要持续强化政策引导、深化场景开放、优化服务供给，推动工业大模型在更广 范围、更深层次赋能安徽制造业提质增效和转型升级。 本次会议以"AI赋能 皖美智造"为主题，集中发布首批23个工业大模型，开展典型案例分享与对接交 流，标志着我省工业大模型发展从技术探索迈向体系化、规模化应用的新阶段。 ...

1月26日上午，广东省十四届人大五次会议开幕，最新出炉的广东省政府工作报告明确提出，强化企业 创新主体地位，加强原始创新和关键核心技术攻关，推进人工智能全域全时全行业高水平应用等举措。 面对新一轮科技革命和产业变革，广东如何进一步激发科技创新的"新动能"？今年广东两会期间，南都 N视频邀请多位专家共读政府工作报告，为广东科技创新建言献策。 加强原始创新和关键核心技术攻关 筑牢科技发展"硬支撑" 原始创新是科技创新的源头，也是摆脱关键技术受制于人的根本。报告提出，要加强原始创新和关键核 心技术攻关。 "加强原始创新和关键核心技术攻关，对广东而言，是关乎国家战略使命、区域竞争格局和未来发展根 基的重大抉择。"广东省政协常委、省工商联常委、粤港澳大湾区青年总会主席吴学明认为，原始创新 和关键核心技术突破是催生新产业（300832）、新模式、新动能的源头活水。 吴学明表示，虽然广东产业体系完整，但在部分关键领域仍存在"卡脖子"风险。加强原始创新，旨在掌 握更多具有自主知识产权的关键核心技术，抢占科技发展制高点，不断催生新质生产力，从而在全球产 业链和价值链中占据更加主动的位置。 实现这一目标的关键点在哪里？广东省政协 ...

1月26日上午，广东省十四届人大五次会议开幕，最新出炉的广东省政府工作报告明确提出，强化企业创新主体地位，加强原始创新和关键核心技术攻关， 推进人工智能全域全时全行业高水平应用等举措。 吴学明表示，虽然广东产业体系完整，但在部分关键领域仍存在"卡脖子"风险。加强原始创新，旨在掌握更多具有自主知识产权的关键核心技术，抢占科技 发展制高点，不断催生新质生产力，从而在全球产业链和价值链中占据更加主动的位置。 实现这一目标的关键点在哪里？广东省政协常委、佳都科技集团董事长兼执行总裁陈娇认为，加强原始创新和核心技术攻关，对广东而言，是从"应用创新 高地"向"源头创新策源地"跃升的必然选择，关键在于"集中力量"和"优化生态"。 面对新一轮科技革命和产业变革，广东如何进一步激发科技创新的"新动能"？今年广东两会期间，南都N视频邀请多位专家共读政府工作报告，为广东科技 创新建言献策。 加强原始创新和关键核心技术攻关 筑牢科技发展"硬支撑" 原始创新是科技创新的源头，也是摆脱关键技术受制于人的根本。报告提出，要加强原始创新和关键核心技术攻关。 "加强原始创新和关键核心技术攻关，对广东而言，是关乎国家战略使命、区域竞争格局和未来 ...

不同于新兴产业和未来产业，传统制造业的数智化转型并非"从0到1"，而是"从有到优"的存量改造。进 一步加快传统制造业转型，扭转部分企业不愿转、不敢转、不会转的局面，需在产业生态构建、企业深 度融合、技术创新突破等方面施策。 构建产业生态。分产业、分等级、分阶段推进数智化转型，构建"先进企业聚力创新、中小企业生态共 享"的产业链协同格局。支持先进企业加快工业互联网、智能体工厂、工业大模型等系统建设，打造具 有行业引领力的标杆范式，带动上下游企业协同创新。推动中小企业开展技术对标与制造思维革新，增 强转型主动性，通过分级分类布局解决"不愿转"问题，以政策支持与创新金融双轮驱动破解"不敢转"难 题，依托示范引领与标准建设突破"不会转"困境，构筑多梯度企业共融共生的智能产业集群。 工业和信息化部、中央网信办、国家发展改革委等8部门前不久联合印发《"人工智能+制造"专项行动实 施意见》，加快推进人工智能技术在制造业中的融合应用，打造新质生产力，全方位、深层次、高水平 赋能新型工业化。传统制造业作为我国制造业的主体，是现代化产业体系的基底。推进这一领域的数智 化转型，是我国从制造大国迈向"智造"强国的必由之路。 "十四五 ...

当前，中国制造业正处于"十五五"规划开局之年与全球产业格局深度重构的历史交汇点，智能制造作为 新一轮产业变革的核心驱动力，已成为制造业转型升级的关键支点，也是新质生产力发展的重要方 向。"十五五"规划建议稿提出，要"推动技术改造升级，促进制造业数智化转型，发展智能制造、绿色 制造、服务型制造，加快产业模式和企业组织形态变革"。 《报告》特别强调，工业大模型已成为智能化转型的核心引擎。中国工业大模型应用市场规模预计将以 23%的年复合增长率持续扩张。《报告》提出智能制造面向2030年发展的六大趋势，整体看，相关趋势 包括，工业大模型驱动制造业从技术突破到产业重构、"人机共生"智能制造生态轮廓日益清晰、工业元 宇宙推动虚拟制造全球化、供应链安全与国产替代双轮驱动产业升级、梯度培育机制推动智能工厂规模 化、标准化落地等。 从"人机共生"的角度，《报告》认为人机协同进入"认知智能"新阶段。中国工业机器人销量稳居全球第 一，协作机器人出货量突破4万台，从传统搬运向空中、水下、地下等非结构化环境全域延伸，纯视觉 定位系统更成功替代人工执行地下管廊等高危巡检任务，实现安全与效率的双提升。 毕马威中国战略及交易咨询合伙人康琦 ...

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The issuance of the "AI + Manufacturing" action plan aligns with global industrial competition and domestic manufacturing transformation needs, aiming to empower the manufacturing sector with AI technology and establish a new quality productivity base [2][4] - The plan emphasizes the integration of AI into manufacturing processes, which is seen as a critical driver for enhancing China's competitive advantage in core technologies and industrial scale [4][10] - The report outlines a comprehensive development system that includes technical support, scenario empowerment, product innovation, ecological activation, and safety assurance [7][9] Summary by Sections Background and Core Positioning - The deep integration of AI and manufacturing is essential for reshaping industrial advantages and seizing development opportunities amid global competition [4] - The plan aims to accelerate the application of AI in manufacturing, addressing the long-standing issues of "large but not strong" in China's manufacturing sector [4][6] Key Policy Interpretations - The action plan focuses on precise implementation and deep advancement from "AI+" to "manufacturing empowerment," targeting specific sectors and processes within the manufacturing industry [5][6] - It sets a goal for China to achieve reliable supply of key AI technologies and maintain a leading position in industrial scale and empowerment levels by 2027 [6][10] Core Measures - The report identifies five core measures to build a comprehensive development system, including: - **Innovation Foundation**: Establishing a full-chain technical support system for AI in manufacturing [7] - **Intelligent Upgrade**: Promoting deep empowerment of AI across all processes and industries [8] - **Product Breakthrough**: Encouraging the iteration and upgrade of intelligent equipment and new business models [8] - **Ecological Cultivation**: Activating collaborative innovation among market entities [9] - **Safety Assurance**: Building a multi-dimensional safety protection system [9] Practical Implications - The action plan addresses the mismatch between computing power supply and manufacturing demand, emphasizing the need for practical applications of AI technologies [10] - It aims to facilitate a fundamental shift in manufacturing from factor-driven to innovation-driven growth, enhancing quality and efficiency [10][13] Challenges and Outlook - The report acknowledges challenges in the deep integration of AI and manufacturing, including performance limitations of industrial models and data fragmentation [11][12] - It anticipates that by 2027, 500 typical application scenarios will be established, leading to scalable implementations in key areas [13]

Investment Rating - The report does not explicitly provide an investment rating for the industry but emphasizes the strategic importance of AI in manufacturing and its potential to enhance competitiveness on a global scale [4][10]. Core Insights - The issuance of the "AI + Manufacturing" action plan aligns with global industrial competition and domestic manufacturing transformation needs, aiming to empower manufacturing through AI technology [2][4]. - The plan focuses on creating a comprehensive development system that includes technology support, scenario empowerment, product innovation, ecosystem activation, and security assurance [7][10]. - By 2027, the plan aims for China's AI core technologies to achieve reliable supply, with the industry scale and empowerment level ranking among the world's top [6][13]. Summary by Sections Background and Core Positioning - The deep integration of AI and manufacturing is essential for reshaping industrial advantages and seizing development opportunities amid global competition [4]. - The plan is a response to the urgent need for China's manufacturing sector to upgrade and transition from scale expansion to quality and efficiency [4][5]. Key Policy Interpretations - The plan introduces five core measures to build a comprehensive development system, focusing on technology support, scenario empowerment, product innovation, ecosystem activation, and security assurance [7][9]. - It emphasizes the need for a dual-cycle empowerment system that connects technology supply and industrial application, fostering a collaborative ecosystem [6][10]. Challenges and Outlook - The report identifies challenges such as the need for real-time response capabilities in industrial models and the fragmentation of industrial data, which hinders model training accuracy [11][12]. - In the short term (1-2 years), the manufacturing sector is expected to enter a phase of benchmark leadership, with 500 typical application scenarios becoming replicable and scalable [13]. - In the long term, the AI-driven innovation ecosystem is projected to enhance China's global competitiveness in core technologies and industry scale, leading the global manufacturing sector towards intelligent transformation [13].

Investment Rating - The report assigns an "Accumulate" rating for the industry [4][33]. Core Insights - The report emphasizes the integration of AI and industrial manufacturing, highlighting the transition from "perceptual interconnection" to "deep intelligence" through policies that promote the development of industrial internet platforms [2][21]. - It outlines four major innovative actions proposed by the policy: platform cultivation, data intelligence enhancement, large-scale application, and ecological support, focusing on the deep integration of AI and industrial internet [2][10]. Summary by Sections 1. Policy Overview and Key Indicators - The report discusses the "Action Plan for Promoting High-Quality Development of Industrial Internet Platforms (2026-2028)" issued by the Ministry of Industry and Information Technology, defining industrial internet platforms as crucial for data aggregation, model accumulation, and application development [8]. - By 2028, the plan aims for over 450 influential platforms, more than 120 million industrial device connections, and a platform penetration rate exceeding 55% [9]. 2. Four Major Action Frameworks 2.1. Platform Cultivation - The report advocates for differentiated platform development, focusing on professional, industry-specific, and collaborative platforms to enhance digital product and service supply [10][12]. - It promotes a "small, fast, light, and precise" approach to digital solutions, transitioning from project-based to subscription-based models [10]. 2.2. Data Intelligence Enhancement - The report highlights the need to improve data collection and integration capabilities, establishing a robust industrial data labeling system and exploring new data management models [13][14]. - It encourages the development of a high-quality industrial model system and supports the "Model as a Service" (MaaS) approach [14][15]. 2.3. Large-Scale Application - The report emphasizes the importance of applying digital management and intelligent production models in traditional industrial settings, particularly for small and medium-sized enterprises [16][17]. 2.4. Ecological Support - The report calls for the establishment of an open-source community for industrial internet platforms and the development of a new standard system to enhance security and data management [19][20]. 3. AI + Manufacturing - The report outlines the synergy between various policies aimed at integrating AI into manufacturing, with specific targets for the development of industrial intelligent entities and high-quality data sets by 2028 [21][22]. - It notes a rapid increase in the penetration rate of industrial intelligent entities, indicating a shift from experimental phases to widespread application across multiple scenarios [22]. 4. Investment Recommendations - The report recommends focusing on companies such as Zhongkong Technology, Rilian Technology, and others, while suggesting to pay attention to companies like Weihong Co. and Rongzhi Rixin [23].

Core Insights - The report emphasizes that industrial large models have become the core engine for intelligent transformation in manufacturing [1] - It outlines six trends for smart manufacturing development towards 2030, including the shift from technical breakthroughs to industrial restructuring driven by industrial large models [1] Group 1: Trends in Smart Manufacturing - The development strategy of China's manufacturing industry is shifting from "efficiency first" to a balance of "safety, controllability, and efficiency" [1] - Advanced technologies such as artificial intelligence are fostering numerous industrial breakthroughs, leading to the intelligent, high-end, and green transformation of manufacturing [1] - The integration of industrial internet, big data, artificial intelligence, and robotics is driving the evolution of manufacturing processes towards intelligence, personalization, and flexibility [1] Group 2: Human-Machine Collaboration - Human-machine collaboration is entering a new stage of "cognitive intelligence," with China maintaining the world's largest industrial robot sales [2] - The shipment of collaborative robots is expected to exceed 40,000 units in 2024, expanding from traditional handling to unstructured environments like aerial, underwater, and underground applications [2] - Companies that possess long-term competitiveness are those that can integrate the "perception-decision-execution-feedback" loop and build industry knowledge bases [2] Group 3: Industry Landscape and Future Outlook - The "Smart Manufacturing Technology 50" selection will officially start in May 2025, open to enterprises in the smart manufacturing technology sector nationwide [2] - Over 70% of the listed companies are in the smart manufacturing and robotics sectors, with nearly half being growth-stage companies established 6 to 10 years ago [2] - The report indicates a regional distribution pattern of "Eastern leadership and Central-Western rise" in the smart manufacturing landscape [2] - The manufacturing industry is evolving towards a new industrial era characterized by efficiency, intelligence, and sustainability [2]