城市制造业高质量发展研究报告 中国信息通信研究院信息化与工业化融合发展研究所 2025年12月 城市制造业高质量发展研究报告 （2025 年） 中国信息通信研究院 2025 年 11 月 （2025 年） 版权声明 本报告版权属于中国信息通信研究院，并受法律保护。 转载、摘编或利用其它方式使用本报告文字或者观点的， 应注明"来源：中国信息通信研究院整理"。违反上述声 明者，本院将追究其相关法律责任。 前 言 党的二十届四中全会进一步强调"因地制宜发展新质生产力" "保持制造业合理比重，构建以先进制造业为骨干的现代化产业体 系"，制造业高质量发展站上更加突出的战略位置。城市作为创新 的策源地，是技术创新、要素创新、产业创新、模式创新的主阵地， 更是因地制宜发展新质生产力的主战场，要更大程度上发挥城市作 为区域"增长极"的引领示范作用。2025 年中央城市工作会议进一 步明确城市发展"从大规模增量扩张阶段转向存量提质增效为主的 阶段"，这对城市制造业高质量发展提出全新要求。同时百年变局 加速演进下城市制造业高质量发展也迎来动能转变、布局优化、目 标升级、路径创新的新机遇。在此背景下，本报告以创新、协调、 绿色、开 ...

政务智能体发展研究报告 (2025 年) 中国信息通信研究院泰尔终端实验室 北京大学公共政策研究中心 2025年12月 版权声明 本报告版权属于中国信息通信研究院、北京大学，并 受法律保护。转载、摘编或利用其它方式使用本报告文字 或者观点的，应注明"来源：中国信息通信研究院、北京 大学"。违反上述声明者，编者将追究其相关法律责任。 前 言 党和国家高度重视政务领域人工智能的应用与治理，《关于深 入实施"人工智能+"行动的意见》和《政务领域人工智能大模型 部署应用指引》等文件在明确安全稳妥有序推进人工智能在政务领 域应用的同时，也提出要鼓励探索政务智能体、具身智能等创新应 用。当前，政务智能体应用探索持续推进，将大模型能力与政务场 景深度结合，在任务理解、流程再造、服务优化、决策支持等方面 展现出巨大潜力，正成为推动政务智能化发展的重要抓手。 报告主要从五方面展开深入分析： 发展背景与定义层面，报告指出，政务智能体的发展是供给侧 大模型与智能体技术进步、需求侧政府治理与公共服务需求升级、 政策端人工智能顶层设计与政策引导共同作用的结果。政务智能体 是指嵌入政府治理和公共服务体系，能够自主感知环境、独立决策、 调 ...

No.202504 无线经济发展研究报告 （2025 年） 中国信息通信研究院 2025年11月 版权声明 本报告版权属于中国信息通信研究院，并受法律保护。 转载、摘编或利用其它方式使用本报告文字或者观点的， 应注明"来源：中国信息通信研究院"。违反上述声明者， 本院将追究其相关法律责任。 前 言 无线经济作为数字经济的关键构成，是创新活力最盛、增长势 头最猛、辐射范围最广的领域之一，在强化数字经济发展新动能、 夯实发展韧性、推动经济实现良性循环方面作用显著，更是推动产 业深度转型、拓展经济增长空间的重要依托。回顾 2024 年，我国无 线经济整体规模持续攀升，在移动通信、低空经济、卫星互联网、 智能网联汽车、具身智能等领域成果丰硕，从技术创新到产业落地， 无线经济正以多元场景应用推动数字经济与实体经济深度融合，在 塑造中国产业发展新优势中发挥了重要作用。具体表现在： 一是无线经济以进促稳。2024 年，我国无线经济规模达到 7.9 万亿元，同比增长 11.1%，占我国 GDP 比重 5.9%，有效支撑数字经 济稳定增长。 二是无线产业和赋能齐头并进。2024 年，我国无线产业规模达 到 3.4 万亿元，占无 ...

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The video codec technology is crucial for processing massive video data, driving the development of the digital visual industry [6] - The evolution of video codec standards is closely tied to patent management, influencing both the efficiency of technology dissemination and the healthy development of the industry ecosystem [6][7] - The report analyzes the global landscape of standard-essential patents (SEPs) and standard proposals in the video codec field, focusing on H.264/AVC, H.265/HEVC, and H.266/VVC standards [8] Summary by Sections Video Codec Standardization and Industry Development - The market has formed a diversified video codec standard ecosystem influenced by technological evolution, commercial competition, and geopolitical factors [16] - The three main standard camps are H.26x/MPEG-x, AVS, and AVx, each playing a significant role in the global video codec market [27] Video Codec Industry Application - Video codec technology impacts various sectors, including streaming services, video conferencing, digital TV broadcasting, and video surveillance [28] - H.26x/MPEG-x standards are widely used across all application scenarios, while AVS standards are primarily applied in China, and AVx standards are gaining traction in the streaming domain [35] Standard-Essential Patent Utilization - The video codec field has two main patent pool management organizations: Via Licensing Alliance and Access Advance, managing SEPs for H.264/AVC and H.265/HEVC standards [37] - The report highlights the increasing frequency of SEP licensing disputes, which are expanding beyond traditional device manufacturers to include content providers [49]

信息无障碍动态 （2025 年 第 10 期） 中国信息通信研究院 | 1 1 | | | | --- | --- | --- | | 1 4 ラ | 1 | | | 1 | | | | 1 1 | ज | | | | | 一、中央动态 1. "十五五"规划建议发布：健全养老事业和产业协同发 展政策机制 10 月 28 日，中共中央关于制定国民经济和社会发展第 十五个五年规划的建议发布。 建议指出，积极应对人口老龄化，健全养老事业和产 业协同发展政策机制。优化基本养老服务供给，完善城乡 养老服务网络，加强公共设施适老化和无障碍改造。发展 医育、医养结合服务。推行长期护理保险，健全失能失智 老年人照护体系，扩大康复护理、安宁疗护服务供给。稳 妥实施渐进式延迟法定退休年龄，优化就业、社保等方面 年龄限制政策，积极开发老年人力资源，发展银发经济。 （信息来源：新华社） 二、部委动态 1 色活动联动、各类主体共同参与的方式，集中开展一系列 形式多样、内容丰富的优质老年用品促消费活动，营造孝 老爱老的社会氛围。部署了提升优质产品供给水平、打造 线上消费新平台、布局线下体验新场景、加强供需双方精 准对接、创新开展主题服务 ...

Report Industry Investment Rating No relevant content provided. Core Views of the Report - The report focuses on the empowerment of intelligent computing centers, elaborating on the latest development trends around demand scenarios, key capabilities, and implementation ecosystems to further release the empowerment effect of intelligent computing centers and promote the deep integration of AI and the real economy [5]. - Facing the "14th Five-Year Plan", the artificial intelligence computing infrastructure has three important development trends: clear demand scenarios for optimal resource allocation, focused key capabilities for improved service levels, and aggregated implementation ecosystems for accelerated value release [24]. - In the future, the demand scenarios of artificial intelligence computing infrastructure will become more diverse and complex, key capabilities will be more intensive and soft, and the implementation ecosystem will be more aggregated and collaborative [75]. Summary by Directory 1. Evolution Trend of Artificial Intelligence Computing Infrastructure - **Technological Innovation: Upgrading of Tri - in - One Intelligent Computing Facilities**: China's artificial intelligence computing infrastructure is evolving towards large - scale clustering, green and low - carbon development, and high - speed interconnection. For example, Huawei's Ascend 384 super - node and ZTE's Nebula intelligent computing super - node achieve high - speed interconnection of computing cards; the liquid - cooling technology in the China Mobile data center reduces energy consumption [12][13][14]. - **Layout Optimization: Coordinated Development of National Intelligent Computing Facilities**: Policy guidance promotes the high - quality development of intelligent computing centers. The scale of intelligent computing centers continues to grow, and regional intelligent computing is deployed in a more coordinated and intensive manner. For instance, as of June 2025, the total rack scale of computing centers in use in China reaches 1.085 million standard racks, and the intelligent computing scale is 788 EFlops [16][17]. - **Industrial Upgrade: Collaborative Development of the Entire Intelligent Computing Industry Chain**: The intelligent computing industry is growing rapidly, with upstream hardware achieving domestic breakthroughs, mid - stream facilities being built on a large scale, and downstream applications accelerating penetration into various industries. Three major operators and AI giants are actively deploying intelligent computing [18][19][20]. 2. Important Trends in the Empowerment of Artificial Intelligence Computing Infrastructure - **Clearer Demand Scenarios for Optimal Allocation of Intelligent Computing Resources**: The positioning of demand scenarios is becoming clearer, promoting the precise empowerment of intelligent computing centers. The construction of artificial intelligence computing infrastructure is shifting from "building well" to "using well", and the rights and responsibilities of all parties are becoming more explicit [25]. - **Focused Key Capabilities for Improved Intelligent Computing Service Levels**: The supply of key capabilities is being strengthened. In terms of basic support, innovation services, and operation guarantee, the service capabilities of intelligent computing centers are continuously improving, promoting the value - closed - loop and long - term development of intelligent computing centers [26][27]. - **Aggregated Implementation Ecosystems for Accelerated Release of Intelligent Computing Value**: The ecological system is being integrated, and the collaborative mechanism is being improved. The construction of artificial intelligence computing infrastructure is evolving towards an integrated solution of "computing power + algorithm + data + scenario + service", and a sustainable and high - value partner network is being initially established [28]. 3. Demand Scenarios of Artificial Intelligence Computing Infrastructure - **Large - Model Pre - training Scenario**: Training large - scale pre - trained models (with over a thousand billion parameters) requires high - end ten - thousand - card cluster centers with E - level computing capabilities. Domestic operators and AI manufacturers are actively building such clusters [30][31][33]. - **Large - Model Fine - tuning Scenario**: Small - scale intelligent computing centers (with a computing capacity of 100 PFlops) can effectively support the fine - tuning of industry models. Most domestic intelligent computing centers are focusing on this scenario [34][36]. - **Large - Model Inference Scenario**: Cloud - side inference dominates the current inference demand scenarios. Different inference application scenarios have different requirements for inference models and intelligent computing centers, and specialized intelligent computing centers for inference are emerging [37][39][40]. 4. Key Capabilities of Artificial Intelligence Computing Infrastructure - **Basic Support Capabilities**: Training scenarios focus on cluster computing power effectiveness, stability, single - cluster computing power scale, and compatibility with mainstream computing frameworks. Inference scenarios focus on throughput, latency, and the heterogeneity of intelligent computing cards [44][45][46]. - **Innovative Service Capabilities**: Training scenarios emphasize high - efficiency cloud services, efficient model migration, and diverse data governance. Inference scenarios focus on the pooling and scheduling capabilities of intelligent computing resources and efficient model migration and deployment [50][51][52]. - **Operation Guarantee Capabilities**: Both training and inference scenarios focus on the flexibility of computing power scheduling, the cost - effectiveness of computing power leasing, and security and compliance. Training scenarios also pay attention to the richness of cooperative partners [55][56][57]. 5. Implementation Ecosystem of Artificial Intelligence Computing Infrastructure - **Collaboration between Intelligent Computing and Data Elements**: Collaborating closely with high - value data is the core for intelligent computing centers to improve basic support capabilities. For example, the Wenzhou Artificial Intelligence Computing Center and the Guian New Area are promoting the transformation of high - quality data resources into intelligent computing ecological capabilities [60][61]. - **Collaboration between Intelligent Computing and Algorithm Models**: Collaborating with high - level algorithm models is the key for intelligent computing centers to improve innovative service capabilities. For example, the Chongqing Artificial Intelligence Innovation Center and the Wuling Mountain (Lichuan) Artificial Intelligence Computing Center are promoting the development and application of industry - specific models [63][64][65]. - **Collaboration between Intelligent Computing and Cross - domain Intelligent Computing**: Promoting cross - domain intelligent computing interconnection and collaboration is an important exploration for the improvement of intelligent computing center operation capabilities. Operators' intelligent computing centers have achieved practical breakthroughs in long - distance interconnection [66][67]. - **Collaboration between Intelligent Computing and Industry Scenarios**: Collaborating closely with industry scenarios is the core driving force for the continuous evolution and upgrading of the intelligent computing center ecosystem. The Chang'an Automobile Intelligent Computing Center and the Yunnan Communications Investment Intelligent Computing Center are typical examples of in - depth collaboration [68][70]. - **Collaboration between Intelligent Computing and Regional Industries**: Collaborating with regional industries is an important guarantee for intelligent computing centers to achieve multi - dimensional and full - scenario empowerment. Intelligent computing centers in Ningbo, Wuhan, and Dalian are promoting regional industrial development [71][73]. 6. Development Outlook - **More Diverse and Complex Demand Scenarios**: The demand scenarios of artificial intelligence computing infrastructure will become more diverse, complex, and deeply integrated. There will be higher requirements for computing power, storage, industry integration, and cloud - edge - end collaboration. Different stakeholders should play different roles [76][77]. - **More Intensive and Soft Key Capabilities**: The artificial intelligence computing infrastructure is shifting from extensive hardware stacking to refined service improvement, including large - scale clustering, resource pooling, open - source development, and service - orientation. Industry organizations and operators should take corresponding measures [78][79][80]. - **More Aggregated and Collaborative Implementation Ecosystems**: The implementation of artificial intelligence computing infrastructure empowerment depends on a more aggregated and collaborative ecosystem, including multi - party participation, joint innovation, and industrial cultivation. Government departments and operators should play their roles [81][82][83].

信息无障碍动态 （2025 年 第 11 期） 中国信息通信研究院 本期导读 | 本期导读 一、中央动态 1 | | --- | | 1. 国务院常务会审议通过《全民阅读促进条例（草案）》1 | | 二、部委动态 1 | | 1. 工信部等六部门联合发文增强消费品供需适配性进一步 | | 促进消费 1 | | 2. 民政部、中国残联召开全国重度残疾人托养照护服务工 | | 作推进视频会 2 | | 3. 国家市场监管总局和民政部联合召开《养老服务标准 | | 体系建设指南（2025 版）》专题新闻发布会 3 | | 三、地方进展 4 | | 1. 第八届中国国际进口博览会上海举办 4 | | 2. 第十一届中国国际老龄产业博览会、残特奥会"科技助 | | 残"博览会开幕 5 | | 3. 适老助残黑科技亮相第三十届中国天津投资贸易洽谈会5 | | 四、企业及社会团体行动 6 | | 1. "科学无障碍共享行动"主题活动在中国科技馆举办 . 6 | | 2. 科技助残 AI 向善，联通在线牵头启动科技助残新生态 7 | | 3. 中国标准化协会与京东集团签署适老化标准战略合作协 | | 议 7 | 一、中央动态 ...

Investment Rating - The report indicates a positive outlook for the domestic smartphone market, with a growth forecast for 5G smartphone adoption and overall market expansion [1][4]. Core Insights - In September 2025, the domestic smartphone shipment reached 27.93 million units, representing a year-on-year increase of 10.1%, with 5G smartphones accounting for 86.3% of total shipments [1]. - From January to September 2025, the total smartphone shipments were 220 million units, showing a slight decline of 0.3% year-on-year, while 5G smartphone shipments increased by 0.1% to 187 million units, maintaining an 85.3% share [1]. - The number of new smartphone models launched in September 2025 was 47, a 30.6% increase year-on-year, with 5G models making up 48.9% of the new launches [3]. - The domestic brands accounted for 84.7% of the total smartphone shipments in September 2025, with a year-on-year growth of 16.1% [4]. Summary by Sections Domestic Smartphone Market Overview - In September 2025, 5G smartphone shipments reached 24.11 million units, a growth of 8.0% year-on-year, contributing to 86.3% of total shipments [1]. - For the first nine months of 2025, 5G smartphone shipments were 187 million units, with a marginal growth of 0.1% [1]. New Smartphone Models - The total number of new smartphone models launched in the first nine months of 2025 was 398, with 180 being 5G models, which is a 1.1% increase year-on-year [3]. Domestic Brand Performance - Domestic brands saw a shipment of 23.64 million units in September 2025, marking a 16.1% increase year-on-year, and accounted for 91.7% of new models launched [4]. Smart Phone Development - In September 2025, smart phone shipments were 25.62 million units, reflecting an 8.0% year-on-year growth, while the number of new smart phone models launched was 29, a significant increase of 52.6% [7].

Report Industry Investment Rating There is no information provided regarding the report's industry investment rating. Core Viewpoints of the Report The report is a collection of typical cases of digital transformation in the manufacturing industry in 2025. It is organized by the China Academy of Information and Communications Technology on behalf of the Ministry of Industry and Information Technology. The collection includes 59 typical cases, covering 15 city cases, 9 park and cluster cases, and 35 enterprise cases. The goal is to promote the digital transformation of the manufacturing industry by sharing successful experiences and practices [6]. Summary by Directory City Chapter - **Hebei Tangshan**: Aims to build a new industrial base in the Bohai - Rim region. It promotes digital transformation through policy planning, pilot construction, and digital industry development. It has achieved results in pilot demonstration, platform construction, and 5G application [19][21][24]. - **Shanghai Songjiang**: Promotes the digital transformation of small and medium - sized enterprises by building a top - level closed - loop mechanism, a three - level linkage system, a precise service resource pool, an innovative publicity matrix, and a public service platform. It has enhanced digital service supply, promoted transformation, and built intelligent manufacturing factories [28][30][35]. - **Jiangsu Changzhou**: Adopts a "rating - diagnosis - improvement - training - chain" approach to solve the problems of enterprises' reluctance, fear, and inability to transform. It has achieved policy support, demonstration effects, and strengthened infrastructure [42][44][49]. - **Zhejiang Ningbo**: Explores a "4M" work path (Method + Machine + Material + Man) to empower the digital transformation of the manufacturing industry with artificial intelligence. It has made achievements in industry demonstration, intelligent equipment, data elements, and talent aggregation [57][60][65]. - **Zhejiang Huzhou**: Drives green intelligent manufacturing with digital and intelligent technologies, constructs a "1 + 3+N" work system, and promotes the digital transformation of the traditional manufacturing industry. It has led in AI application, achieved significant digital transformation in characteristic industries, and is at the forefront in digital - green integration [73][75][78]. - **Anhui Wuhu**: Promotes the digital transformation of enterprises through top - level design, optimizing the transformation ecosystem, pilot demonstration, and creating a transformation atmosphere. It has cultivated many intelligent factories and platforms [87][89][94]. - **Fujian Quanzhou**: Improves the "government - enterprise - service" transformation ecosystem to promote the digital transformation of manufacturing enterprises. It has advanced digital transformation and improved the transformation ecosystem [99][101][107]. - **Jiangxi Yingtan**: Integrates "policy - technology - finance - service" elements to achieve cluster - based digital transformation. It has created digital transformation benchmarks, built a provincial "copper industry brain", and strengthened talent support [112][114][118]. - **Shandong Jinan**: Implements a digital transformation action with a 16 - character working method. It has promoted network infrastructure construction, project development, and the emergence of pilot demonstrations [125][127][131]. - **Henan Luoyang**: Solves the problems of enterprises' reluctance, fear, and inability to transform through various measures such as changing concepts. It has formed a good situation where leading enterprises lead and small and medium - sized enterprises follow [141][143]. Park and Cluster Chapter - **Suzhou Industrial Park**: Focuses on building a high - standard digital park with intelligence, data, and networking [12]. - **Hangzhou High - tech Industrial Development Zone**: Integrates resources, strengthens mechanisms, and builds platforms to promote the digital transformation of large - scale industrial enterprises [12]. - **Hefei New Station High - tech Industrial Development Zone**: Empowers the digital transformation of the "chip" and "screen" industries with digital and intelligent technologies [12]. - **Shangrao Economic and Technological Development Zone**: Builds an ecological system for digital transformation through "three - dimensional linkage" [12]. - **Zhengzhou High - tech Industrial Development Zone**: Empowers the systematic leap of the manufacturing cluster with "computing power + brain" dual - core drive [12]. - **Chengdu High - tech Industrial Development Zone**: Breaks through the transformation difficulties of small and medium - sized enterprises with financial tools and promotes the "point - line - surface" integrated work of "intelligent transformation and digital transformation" [12]. - **Wuxi Internet of Things Cluster**: Accelerates the construction of a comprehensive digital transformation ability center and promotes the digital transformation of Internet of Things enterprises [12]. - **Wenzhou Yueqing Electrical Cluster**: Promotes the digital transformation of the electrical industry cluster through "chain - based collaboration" [12]. - **Chengde High - end Energy Equipment Cluster**: The chain - leader leads the digital transformation from the "chain" to the "cluster" to activate the high - quality development of the industrial cluster [12]. Enterprise Chapter - **Aviation and Medical GE Healthcare Systems Co., Ltd.**: Digitally empowers the intelligent and flexible manufacturing of high - end CT detectors [14]. - **Taiji Computer Co., Ltd.**: Builds a "full - domain intelligent connection" ecosystem to empower the innovation and development of smart parks [14]. - **China Automotive Data (Tianjin) Co., Ltd.**: Applies large - language model technology to promote the intelligent application of automobile test scenarios [14]. - **CITIC Dicastal Co., Ltd.**: Upgrades the lighthouse with artificial intelligence [14]. - **Shanxi Jinbo Biotech Co., Ltd.**: Applies its self - developed "AI Collagen Brain System" to achieve cost - reduction and efficiency - improvement in the enterprise's full - life - cycle management [14]. - **Harbin Electric Machinery Co., Ltd.**: Applies artificial intelligence and flexible manufacturing technology to build a fully digital and flexible production workshop for stator laminations [14]. - **CSIC Longjiang Guanghan Gas Turbine Co., Ltd.**: Empowers the independent development of the full - life - cycle of gas turbines with full - business - chain digital technology [14]. - **Baowu Equipment Intelligent Technology Co., Ltd.**: Applies an equipment remote intelligent operation and maintenance platform to promote the digital transformation of the steel industry [14]. - **Yangtze River Pharmaceutical Group Co., Ltd.**: Applies artificial intelligence, big data, and the Internet of Things to achieve accurate traceability of drug quality [14]. - **CRRC Nanjing Puzhen Co., Ltd.**: Applies artificial intelligence image processing and deep - learning technology to achieve intelligent remote diagnosis and analysis in multi - professional intelligent operation and maintenance [14]. - **Jiangyin Xingcheng Special Steel Co., Ltd.**: Manages and innovates the special steel process collaboratively based on data elements and artificial intelligence [14]. - **SUPCON Technology Co., Ltd.**: Applies industrial AI technology to help chlor - alkali enterprises achieve low - carbon, cost - reduction, quality - improvement, and efficiency - enhancement [14]. - **Ningbo Orient Cable Co., Ltd.**: Applies trusted technology to achieve energy - conservation and emission - reduction in cable enterprises' energy - carbon management [14]. - **Tongkun Group Co., Ltd.**: Conducts intelligent practices in a "5G full - connected + digital twin" polyester fiber future factory [14]. - **Anhui Gujinggong Wine Co., Ltd.**: Applies 5G + industrial Internet technology to promote the digital and intelligent transformation of the liquor - production scenario [14]. - **Changhong Meiling Co., Ltd.**: Promotes the transformation and upgrading of the smart supply chain based on 5G + industrial Internet technology [14]. - **Fujian Fubusi Textile Co., Ltd.**: Applies industrial Internet and AI technology to achieve cost - reduction, efficiency - improvement, and intelligent production in the textile and fabric industry [14]. - **Jiangxi Weimian Textile Group Co., Ltd.**: Reduces operating costs in intelligent spinning based on AI + visual digital twin [14]. - **Changhe Aircraft Industries (Group) Co., Ltd.**: Builds an intelligent manufacturing workshop for key helicopter machining parts based on digital twin technology [14]. - **Weichai Power Co., Ltd.**: Builds a data - empowered platform for the entire industrial chain to promote the ecological - level collaborative development of high - end power systems [14]. - **Shandong Daiyin Textile Group Co., Ltd.**: Applies intelligent manufacturing technology to achieve international and personalized high - end customization in suit production [16]. - **Kaios Technology (Qingdao) Co., Ltd.**: Applies a group - level industrial Internet platform to improve the enterprise's operation and management capabilities [16]. - **Zhongchuang Zhiling (Zhengzhou) Industrial Technology Group Co., Ltd.**: Builds a lighthouse factory in the coal - mining machinery industry [16]. - **Hunan Taixin Ceramics Co., Ltd.**: Applies industrial vision large - models and digital integration technology to promote the collaborative development of the entire ceramic chain, achieving quality improvement and green emission - reduction [16]. - **Liuyang Yihelong Fireworks Group Co., Ltd.**: Applies a micro - data platform and AIOT technology to achieve intelligent transformation of the high - risk fireworks production industry, improving both safety and production efficiency [16]. - **RootCloud Co., Ltd.**: Applies industrial AI large - model technology to promote the multi - modal large - model application in ship - repair business [16]. - **Foshan Haitian (Gaoming) Flavoring Food Co., Ltd.**: Conducts a digital and intelligent transformation practice in the traditional brewing industry with a "lighthouse factory" [16]. - **Gree Electric Appliances, Inc. of Zhuhai**: Develops a digital ecosystem for controller manufacturing based on artificial intelligence [16]. - **TCL Mobile Communications Co., Ltd.**: Applies digital technology to achieve full - process efficient collaboration and benefit improvement in the intelligent manufacturing of mobile intelligent terminals [16]. - **Guangxi Huasheng New Materials Co., Ltd.**: Applies AI technology to achieve intelligent control in the alumina production process [16]. - **Wide - Area Digital Technology Co., Ltd.**: Applies AI and industrial Internet technology to achieve full - process intelligent energy - conservation, cost - reduction, and efficiency - improvement in the electrolytic aluminum factory [16]. - **Seres Automobile Co., Ltd.**: Applies multi - modal deep - learning technology to online detection and control of new - energy vehicle welding spot quality [16]. - **Guiyang Aero - Engine Precision Casting Co., Ltd.**: Builds a digital and intelligent workshop for the casting of aero - engine directional crystal turbine blades [16]. - **Xi'an Geely Automobile Co., Ltd.**: Applies visual AI technology to promote the entire - process manufacturing [16]. - **Xinjiang Kunlun Zinc Industry Co., Ltd.**: Applies a comprehensive empowerment platform and other technologies to achieve digital and intelligent transformation in the lead - zinc smelting project [16].

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The emergence of high-performance open-source large models has significantly lowered the barriers and costs for AI application innovation, driving the development of intelligent computing applications across various sectors such as finance, government, education, healthcare, and industry [7][14] - The report emphasizes the differentiated network connection requirements arising from the rapid growth of intelligent computing applications, highlighting the need for high bandwidth, low latency, and high reliability to support AI model training and inference [7][15] - The report proposes five key features for high-quality computing dedicated lines tailored for intelligent computing applications: intelligent perception, business certainty experience, elastic network on demand, intelligent operation and maintenance, and optical computing collaboration [7][15] Summary by Sections Overview - The proliferation of open-source large models since 2023 has disrupted the previous monopoly in the field, enabling rapid innovation in intelligent computing applications across various industries [14] - The report identifies the need for networks to perceive business types and provide differentiated connection capabilities to ensure optimal service experiences [14] Differentiated Dedicated Line Service Requirements for Intelligent Computing Applications Financial Intelligent Computing Applications - Financial institutions are leveraging AI for customer service, risk management, and operational efficiency, requiring high bandwidth and low latency for various applications [17][22] - Specific network requirements include: - AI service assistants: 5 Mbps bandwidth, latency < 5 ms, availability ≥ 99.99% [27] - Digital lobby managers: 200 Mbps bandwidth, latency < 2.5 ms, availability ≥ 99.99% [27] - AI financial compliance checks: 150 Mbps bandwidth, latency < 5 ms, availability ≥ 99.99% [27] - AI fraud detection systems: 5 Mbps bandwidth, latency < 5 ms, availability ≥ 99.99% [27] Government Intelligent Computing Applications - The report discusses the transition from basic digitalization to comprehensive intelligent governance, emphasizing the need for flexible network services to handle varying demands [29][33] - Network requirements include: - Intelligent government customer service: < 5 Mbps bandwidth, latency < 500 ms, availability ≥ 99.99% [38] - Intelligent traffic management: < 200 Mbps bandwidth, latency < 20 ms, availability ≥ 99.99% [38] - Intelligent environmental monitoring: 200 Kbps to 20 Mbps bandwidth, latency < 500 ms, availability ≥ 99.99% [38] Educational Intelligent Computing Applications - The report highlights the transformation in education through intelligent computing, with applications in personalized learning and automated assessment [39][43] - Network requirements include: - Smart classrooms: 100-500 Mbps bandwidth, latency < 25 ms, availability ≥ 99.99% [45] - Intelligent monitoring systems: ~4 Gbps bandwidth, latency < 5 ms, availability ≥ 99.99% [45] Healthcare Intelligent Computing Applications - The healthcare sector is increasingly adopting intelligent computing to enhance diagnostic accuracy and operational efficiency [46][49] - Network requirements include: - AI-assisted imaging: 10 Gbps bandwidth, latency < 10 ms, availability ≥ 99.9% [52] - AI-assisted diagnosis: 500 Mbps to 1 Gbps bandwidth, latency < 5 ms, availability ≥ 99.9% [52] Public Security Intelligent Computing Applications - AI is being integrated into public security to enhance risk identification and response capabilities [54][58] - Network requirements include: - AI video monitoring: 200 Mbps bandwidth, latency < 5 ms, availability ≥ 99.99% [60] - AI policing services: 20 Mbps bandwidth, latency < 50 ms, availability ≥ 99.99% [60] Entertainment Intelligent Computing Applications - The report discusses the digital transformation of the entertainment industry, particularly in cloud gaming and media production [66][67] - Network requirements include: - Cloud gaming: 120 Mbps bandwidth per user, latency < 1 ms [66] - 3D scene reconstruction: 1 Gbps bandwidth, latency < 1 ms [67]