盛夏的乌兰察布草原，传统奶香与现代数据流在这里碰撞出高质量发展的火花。作为扎根内蒙古的本土 银行，内蒙古银行用金融活水精准滴灌地方民营经济发展脉络，以创新金融服务为笔，绘就了一幅"产 业+金融"协同发展的新画卷。 内蒙古银行乌兰察布分行相关负责人介绍，这场银企"双向奔赴"源于长期的战略互信。2014年，内蒙古 银行与兰格格乳业正式建立战略合作关系 —— 彼时，银行看中了企业在细分领域深耕多年的专业积 淀，而企业正迫切需要金融力量支撑其智能化转型。双方的合作不仅见证了传统乳业向高端化、智能化 的跃升，更彰显了地方金融机构深耕本土、服务实体的责任担当。 如今，俯瞰兰格格乳业的智能化工厂，智能化生产车间与14条智能生产线交相辉映。在金融活水的持续 滋养下，一场"科技+金融"驱动的产业变革正在草原深处蓬勃生长。 能源基地 数字化转型 在乌兰察布市郊，中金数据算力中心项目的施工现场机器轰鸣，工人们正紧锣密鼓地进行设备安装和调 试。这座占地数百亩的"草原云谷"核心项目，承载着乌兰察布从传统能源基地向数字经济高地转型的雄 心壮志。然而，就在项目推进至关键阶段时，项目方因设备采购与基建工程产生的巨额资金需求，让建 设工作遭遇 ...

Core Viewpoint - The article discusses the IOMM model introduced by the China Academy of Information and Communications Technology (CAICT) as a framework for assessing and guiding enterprises in their digital transformation journey, emphasizing the necessity of digital transformation in the current economy [1][8]. Group 1: Digital Transformation Trends - Digital transformation has shifted from an optional strategy to a mandatory requirement for enterprises due to the rapid integration of cloud computing, big data, and artificial intelligence [1][2]. - Policies have been implemented to encourage enterprises to adopt digital technologies, enhancing their operational processes and production methods [2][3]. Group 2: Nature and Path of Transformation - The essence of digital transformation lies in the comprehensive integration of digital technologies with business elements to optimize resource allocation and improve productivity [3][4]. - Different types of enterprises have distinct transformation paths; IT-driven companies often start with IT infrastructure, while non-IT-driven companies focus on core business processes [3][21]. Group 3: IOMM Model Overview - The IOMM model evaluates enterprises based on two dimensions: digital infrastructure service operation capability and overall digital operational capability [4][5]. - The model consists of five maturity stages for digital infrastructure, ranging from basic assurance to innovation leadership, providing a roadmap for enterprises to assess their current status and identify improvement areas [4][28]. Group 4: Practical Case Studies - Leading enterprises that participated in the IOMM assessment have demonstrated significant advancements in their digital transformation efforts, such as China Construction Bank and Alibaba Cloud, showcasing the effectiveness of the model [6][7]. Group 5: Conclusion and Future Directions - The adoption of the IOMM model marks a transition from chaotic growth to refined operations in digital transformation, emphasizing the importance of aligning digital technologies with value creation [8][26]. - Digital transformation is viewed as an ongoing process rather than a final goal, enabling enterprises to adapt and thrive in the digital economy [8][18].

Core Viewpoint - The "Digital Empowerment of New Consumption Forum" highlighted the integration of advanced technologies like AI and big data into various industries, emphasizing the shift from price sensitivity to value sensitivity in consumer behavior [3][5][11]. Group 1: Industry Insights - The forum discussed the transformation of marketing concepts in the context of digital empowerment, with a focus on creating transparent value models rather than merely selling products [3]. - The apparel industry is experiencing changes due to AI, which may replace certain technical roles but also necessitates new educational directions to enhance talent value in future jobs [5]. - The biopharmaceutical sector is leveraging AI to shorten the R&D cycle for new materials, exemplified by a company that has utilized AI to build a skin microbiome database [9]. Group 2: Company Strategies - Yalu Holdings is transitioning to a digital ecological service platform, restructuring its business model to integrate resources and enhance internal management functions [3]. - Daily Interactive has established a closed-loop business model driven by data, with 90% of its revenue coming from deep data mining and monetization [7]. - The cultural and creative industries are presented with new opportunities through digital communication, as companies can better understand user needs and develop attractive products [11].

Core Viewpoint - Liaoning Province has introduced the "Implementation Plan for Digital Government Construction (2025-2027)" to enhance government governance and service efficiency through digital technologies such as big data and artificial intelligence [1][2] Group 1: Implementation Plan Overview - The plan emphasizes a "whole province in one chessboard" approach, focusing on top-level design and overall promotion of digital government initiatives [2] - Key components include the establishment of a data governance system, data standard system, and the integration of data resources to enhance data sharing and utilization [2][3] Group 2: Infrastructure Development - Liaoning has established a "two places, three centers" provincial data center support system, with 699 information systems migrated to the cloud [3] - The electronic government extranet covers over 27,000 service points across various administrative levels, enhancing accessibility and service delivery [3] Group 3: Future Directions - The province plans to continue promoting cloud migration for non-sensitive government information systems and optimize the management of government cloud resources [4] - Future upgrades will focus on integrating specialized networks with the electronic government extranet, expanding bandwidth, and enhancing data transmission efficiency [4]

Group 1 - The Chinese government has approved the "Artificial Intelligence +" action plan, emphasizing the integration of AI into various sectors and the importance of government-led demonstration projects [1] - The policy shift indicates a transition from technology support to positioning AI as a core engine for economic transformation, with local initiatives like Beijing's "AI-native city" and Shenzhen's "smart driving pioneer" reflecting this trend [1] - Overseas, AI capital expenditures are being revised upwards, with Meta increasing its 2026 capital expenditure guidance to nearly $100 billion and Microsoft planning to invest over $30 billion in the next quarter, primarily targeting AI infrastructure [1] Group 2 - The rapid development of AI is intensifying competition for traffic entry points, with significant hardware investments driving further efficiency in AI applications [2] - Cloud service providers are increasing their investments in computing power, driven by the competition for massive traffic and advertising revenue, with a focus on AI models and intelligent agents to enhance customer engagement [2] - The Big Data ETF closely tracks the CSI Cloud Computing and Big Data Theme Index, which includes 50 companies involved in cloud computing and big data services, reflecting the overall performance of these sectors [2] Group 3 - As of July 31, 2025, the top ten weighted stocks in the CSI Cloud Computing and Big Data Theme Index account for 53.85% of the index, including companies like Zhongji Xuchuang and Keda Xunfei [3]

Group 1 - The seventh International Academic Conference on Artificial Intelligence, Computer Science, and Information Processing (AICSIP 2025) was held in Hangzhou, Zhejiang on July 25 [1] - A paper titled "Explaining The Improvement Of Multi-Exit Structure Distillation Using Stage Training And Attention Integration" was presented by a data intelligence technology company, attracting significant attention from both academia and the tech industry [1] - The research addresses the performance decline and inefficiency issues that arise when original AI models are distilled into smaller, less hardware-intensive models for enterprise applications, proposing a technique that enhances knowledge transfer efficiency during the distillation process [1] Group 2 - The technology has been successfully applied to a cloud-based hydropower model platform, resulting in a 52% reduction in computational consumption and a 40% increase in inference speed for the established runoff time series prediction model compared to pre-distillation [1] - This advancement significantly lowers the hardware resource requirements for AI applications in the hydropower industry, providing strong support for enhancing the intelligence level of hydropower applications [1] - The conference was sponsored by the IEEE China Council and co-hosted by Hangzhou Normal University and Hubei Zhongke Geological and Environmental Technology Service Center, with all accepted papers to be included in the IEEE Xplore core database and submitted for EI Compendex and Scopus indexing, highlighting the academic value and technological forefront of the research [2]

Group 1 - The National Internet Information Office of China has raised concerns regarding security risks associated with NVIDIA's H20 computing chip, prompting the company to provide explanations and proof materials [1] - Following the news, there has been increased market interest in domestic cloud computing and data security sectors, with significant stock price movements in related companies [1] - As of July 31, the Big Data ETF (159739.SZ) rose by 2.39%, and its associated cloud computing index increased by 2.27%, with notable gains in key component stocks such as Zhongji Xuchuang (+4.63%), Yonyou Network (+10.03%), and Kingsoft Office (+4.10%) [1] Group 2 - Northeast Securities highlighted Huawei's comprehensive layout from hardware to industry algorithms, with its Ascend 910C chip achieving FP16 computing power of 752 TFLOPS, supporting AI model training and inference [2] - The report also noted Huawei's collaborations with companies like Sinochem and Xingfa Group in smart manufacturing, demonstrating the practical benefits of AI models in optimizing chemical processes and reducing energy consumption [2] - Additionally, Meta and Google have increased their annual capital expenditure to $85 billion to strengthen AI infrastructure, indicating sustained high demand for global AI computing power and confirming growth momentum in the cloud computing industry [2]

Core Points - The CSI Cloud Computing and Big Data Theme Index rose by 2.26% to 5125.82 points, with a trading volume of 76.683 billion yuan [1] - The index has increased by 10.31% over the past month, 19.25% over the past three months, and 17.46% year-to-date [1] - The index consists of 50 listed companies involved in cloud computing services, big data services, and related hardware [1] Index Composition - The top ten weighted companies in the index are: iFlytek (8.6%), Zhongji Xuchuang (8.44%), Xinyi Sheng (8.35%), Kingsoft Office (5.33%), Zhongke Shuguang (4.95%), Hengsheng Electronics (4.34%), Inspur Information (4.31%), Unisplendour (3.81%), Runhe Software (3.29%), and Runze Technology (2.54%) [1] - The industry composition of the index shows that Information Technology accounts for 65.80%, Communication Services for 33.03%, and Industry for 1.17% [1] Index Adjustment - The index samples are adjusted semi-annually, with adjustments implemented on the next trading day after the second Friday of June and December [2] - Weight factors are generally fixed until the next scheduled adjustment, with temporary adjustments made under special circumstances [2] - Public funds tracking cloud computing include various ETFs and theme funds from different financial institutions [2]

Core Viewpoint - The National Data Bureau is actively promoting the construction of comprehensive data element pilot zones to support local initiatives in data property rights and market ecology, focusing on 35 key experimental tasks across eight areas [2][3]. Group 1: Pilot Zone Construction - The National Data Element Comprehensive Pilot Zones are established to drive the market-oriented allocation reform of data elements, with ten zones set up in various provinces including Beijing, Zhejiang, and Anhui [3]. - The pilot zones aim to address public data aggregation governance and authorized operations, with key tasks including data infrastructure construction and data resource development [3]. Group 2: Regional Initiatives - Guizhou province is leveraging its advantages to enhance the digital economy, implementing policies to promote high-quality data industry development, including a focus on data resource collaboration and incentives for businesses [4]. - Hubei province has deployed AI systems in 170 hospitals, achieving a 95.88% coverage rate for AI-assisted diagnosis, and has built a pathology database with over 2.3 million high-precision digital slices [4]. Group 3: Data Infrastructure Development - Beijing is constructing a data infrastructure system aimed at high-speed interconnectivity and security, with over 4,500 data products launched across various sectors [6]. - Anhui province is advancing its data center construction, attracting significant investment and establishing a comprehensive computing resource platform that integrates various computing types [7]. Group 4: Data Application and Industry Empowerment - Shandong province is focusing on marine data development, creating a specialized marine big data trading platform that has gathered over 12 billion global marine data records [8]. - Guizhou is enhancing the tourism sector through data standardization and application, creating a smart tourism system that integrates various services for visitors [9][10].

Group 1 - The Chinese Ministry of Commerce aims to strengthen traditional energy cooperation with Arab countries while expanding collaboration in renewable energy sectors such as photovoltaics, wind power, and green hydrogen [1] - The upcoming 7th China-Arab States Expo will be held from August 28 to 31 in Yinchuan, Ningxia, with a focus on innovation, green development, and prosperity [2] - In 2024, the trade volume between China and Arab countries is projected to reach $407.4 billion, reflecting a year-on-year growth of 2.3%, maintaining China's position as the largest trading partner of Arab nations [1] Group 2 - Chinese enterprises are actively investing in various production projects in Egypt, UAE, and Saudi Arabia, including metal smelting, building materials manufacturing, cotton spinning, and aquaculture [1] - There is a growing trend of mutual investment, with Arab sovereign wealth funds and companies investing in China's petrochemical, new energy, and technology sectors [1] - The economic structures of China and Arab countries are complementary, with significant potential for future cooperation in traditional sectors like energy, agriculture, and infrastructure, as well as emerging fields such as new energy vehicles, high-end equipment manufacturing, and green low-carbon technologies [1]