Investment Rating - The report does not explicitly state an investment rating for the ASEAN artificial intelligence industry Core Insights - The ASEAN AI market is expected to grow significantly, with the digital economy projected to reach $295 billion by 2025, growing at a compound annual growth rate (CAGR) of 16% [7] - ASEAN countries are accelerating the establishment of a regional AI ecosystem, enhancing cooperation with countries like China, the US, and Japan, which diversifies the global AI industry landscape [7] - The development of AI in ASEAN is expected to contribute significantly to GDP growth, although challenges such as technological infrastructure, talent shortages, and regulatory coordination remain [7] Summary by Sections Current Status and Outlook of the ASEAN AI Industry - The global AI market is projected to reach $1.8 trillion by 2030, with ASEAN actively participating in this growth [7] - The digital economy in Southeast Asia is expected to grow at a CAGR of 27% since 2021, reaching $295 billion by 2025 [9] Development Level - As of 2024, there are significant disparities in AI development levels among ASEAN countries, with Singapore and Malaysia leading, while many others face challenges such as weak technological foundations and talent shortages [9] Policy and Regulations - ASEAN countries are rapidly launching national AI strategies and regulations, aiming for policy integration to strengthen the regional AI development foundation [13] Advantages of Each Country - Singapore and Malaysia focus on fintech and large models, while Thailand and the Philippines apply AI in tourism and services, and countries like Vietnam and Indonesia emphasize AI in industrial and agricultural sectors [14] Local Challenges - The influx of foreign capital and technology, particularly from Chinese tech companies, is driving rapid growth in the digital startup ecosystem in ASEAN [18] Company Introductions - Leading AI companies in ASEAN exhibit strong localization characteristics, deeply integrating with national advantage industries such as finance and public services [22] Development Characteristics - ASEAN's diverse internal market and open cooperation framework are accelerating AI industry development and enhancing its role in global AI governance [23]

Core Viewpoint - The urban trusted data space is a key infrastructure led by the government to promote the development and utilization of urban data resources, serving as a bridge between data supply and application [1][2]. Development Drivers Policy - The establishment of urban trusted data spaces is encouraged through a series of top-level designs and strategic plans aimed at market-oriented data element reforms, with the first batch of 13 pilot cities announced [4][5]. Technology - Privacy computing and blockchain technology are pivotal in addressing the challenges of trusted data circulation, enabling data sharing while ensuring compliance and security [5][6]. Demand - With China's data production expected to exceed 40ZB by 2024, the urban trusted data space is essential for enhancing urban governance efficiency by integrating and utilizing public data resources [8]. Value of Urban Trusted Data Space - The urban trusted data space aims to resolve issues such as the lack of trust mechanisms and inefficient circulation in urban governance, thereby enhancing the efficiency of public data utilization and supporting modern urban governance [11]. Overall Framework - The urban trusted data space is built on a governance cloud infrastructure, allowing secure data access and supporting various applications through a collaborative ecosystem [13]. Core Capabilities - The core capabilities of the urban trusted data space include trusted control, resource interaction, and value co-creation, which are essential for establishing a reliable data circulation infrastructure [16]. Industry Chain and Players - The urban trusted data space involves five main entities: operators, data providers, data users, data service providers, and regulatory bodies, each playing a crucial role in the ecosystem [21]. Competitive Analysis - In the technical service sector, comprehensive and specialized firms compete, with ICT background cloud service providers leading in capabilities [24]. Application Scenarios Government Services - The urban trusted data space facilitates inter-departmental data sharing, enhancing government services and decision-making through improved data accessibility [27]. Inclusive Finance - By integrating government and financial data, the urban trusted data space supports the development of dynamic risk assessment models, promoting inclusive financial services [30]. Case Studies Zhangjiakou Trusted Data Space - The Zhangjiakou trusted data space employs a "one space, four platforms, one system" architecture to support secure data circulation and enhance public data value [33][35]. Shanghai Trusted Data Space - Shanghai's urban trusted data space, leveraging blockchain technology, aims to meet the complex data needs of a megacity, facilitating secure and efficient data utilization [37][39]. Technology Trends - AI is becoming a key driver in enhancing data governance efficiency, transitioning from manual to automated and intelligent governance strategies [42]. Application Trends - The urban trusted data space is evolving from single pilot projects to collaborative ecosystems, attracting industry and enterprise participation to explore vertical applications [44][45].

Core Insights - Guizhou is significantly enhancing its computing power industry, focusing on intelligent computing to support the national "East Data West Computing" strategy and facilitate digital transformation across various sectors [3][4] Group 1: Development of Computing Power - Guizhou has established 50 data centers by 2025, with a total computing power exceeding 150 EFLOPS, nearly doubling from 2024, and over 90% of this capacity is in intelligent computing [3] - The province has become one of the strongest regions in China for intelligent computing capabilities and resources, with 48 computing service providers aggregated at the national integrated computing network hub [3] Group 2: Infrastructure and Network Support - Guizhou has built a robust network infrastructure, including a national-level internet backbone direct connection point and an international internet data dedicated channel, making it one of the few provinces with all three major information infrastructure components [3] Group 3: Collaborative Development and Future Plans - The province is creating a new collaborative development model for the computing power industry, attracting major companies like Huawei Cloud and iFlytek to establish industry-leading projects [4] - Guizhou aims to further enhance the quality of its computing power industry by implementing more substantial measures and attracting additional projects to expand its digital intelligence industry cluster [4]

Core Insights - Guizhou is significantly advancing its computing power industry, focusing on intelligent computing, to support the national "East Data West Computing" strategy and facilitate digital transformation across various sectors [1][2] Group 1: Industry Development - By 2025, Guizhou plans to have 50 data centers in operation, with total computing power exceeding 150 EFLOPS, representing nearly a twofold increase from 2024, and over 90% of this capacity will be in intelligent computing [1] - Guizhou has become one of the regions with the strongest intelligent computing capabilities and the most concentrated resources in the country, with 48 computing service providers aggregated at the national integrated computing network hub [1] Group 2: Infrastructure and Support - The province has established a robust network infrastructure, including a national-level internet backbone direct connection point and an international internet data dedicated channel, making it one of the few provinces with all three major information infrastructure components [1] - The computing power scheduling platform in Guizhou is facilitating cross-regional collaboration and attracting major companies like Huawei Cloud and iFlytek to establish industry-leading model projects [1] Group 3: Future Plans - Looking ahead to the 14th Five-Year Plan, Guizhou aims to enhance the quality of its computing power industry with a focus on intelligent computing, while continuing to attract more data center projects and expand existing ones [2]

Group 1 - Guizhou is focusing on developing a computing power industry centered around intelligent computing, enhancing its comprehensive supply capacity to support the national "East Data West Computing" strategy and facilitate digital transformation across various sectors [1] - By 2025, Guizhou plans to have 50 data centers in operation, with a total computing power exceeding 150 EFLOPS, nearly doubling from 2024, and over 90% of this capacity will be in intelligent computing [1] - The province has established a national integrated computing power network hub, gathering 48 computing service providers and recording a total of 25.85 billion yuan in computing power transactions [1] Group 2 - Guizhou aims to promote high-quality development of the computing power industry with a focus on intelligent computing during the 14th Five-Year Plan, enhancing computing, storage, and transportation capabilities [2] - The province plans to accelerate the expansion of existing data center projects from major internet companies and state-owned enterprises while attracting more projects to grow the digital intelligence industry cluster [2]

5G通信 数十万5G与信息领域关注者的头部科技媒体 近日，中国移动2025年至2026年集中网络云资源池七期工程计算型服务器超大采购订单中标候选人结果 正式公示，本次采购涉及计算型服务器总计8581台，仅目前已公布的两个标包不含税总金额就已达到约 20亿元。 文 赵哲超/5G通信 移动的算力"加码"逻辑 作为行业老兵，我见证了太多运营商的投资周期变化。这次移动的大手笔采购，绝非一时兴起，而是有 着清晰的战略考量。 从财务数据看，2024年中国移动算力领域投入475亿元，同比增长21.5%，占资本开支比重从21.7%提升 至27.5%。这个比例变化很有意思——在总体资本开支下降4%的情况下，算力投资逆势上扬，说明移动 已经把算力当作下一个增长极来布局。 从集采规模看，今年移动的算力采购确实"疯狂"。先是191亿元的AI训练服务器集采，紧接着50亿元的 AI推理服务器集采，现在又来了20亿元的网络云资源池服务器。短短一年内，仅服务器采购就超过260 亿元，这在运营商历史上都是罕见的。并且目前，标包3、4、5的中标候选人尚未公布，意味着此次大 规模集采的最终总金额仍有上升空间。 更关键的是，中国移动时任董事长、党组 ...

Core Viewpoint - The stock of Aidi Kang Holdings (09860) has increased by over 5%, with a cumulative rise of 20% over the past three trading days, reflecting positive market sentiment towards AI in the healthcare sector [1] Group 1: Market Performance - Aidi Kang's stock price rose by 5.68% to HKD 5.4, with a trading volume of HKD 17.98 million [1] Group 2: Industry Developments - Recent favorable developments in the AI healthcare sector include a partnership between NVIDIA and Eli Lilly, committing USD 1 billion to establish a joint research lab in the San Francisco Bay Area over the next five years [1] - OpenAI announced the acquisition of healthcare tech startup Torch, indicating a growing interest in AI applications within the medical field [1] - Domestic AI healthcare applications are also accelerating, with Ant Group's AI healthcare product, Aifu, surpassing 15 million monthly active users, and major internet companies like ByteDance, Baidu, JD.com, and Tencent making significant investments in this area [1] Group 3: Company Collaborations - Aidi Kang signed a cooperation agreement with Huawei Cloud in December 2025, marking a new phase in collaborative innovation in smart healthcare [1] - The partnership aims to integrate AI technology into healthcare services, transitioning from traditional models to intelligent and ecological systems, representing a significant milestone in medical testing services [1]

艾迪康控股(09860)再涨超5%，近三个交易日累涨两成。截至发稿，涨5.68%，报5.4港元，成交额 1798.16万港元。 消息面上，近期AI医疗领域利好催化密集。英伟达与美国制药巨头礼来当地时间周一宣布，双方将在 未来五年内投入10亿美元，在旧金山湾区建设一座联合研究实验室，旨在加速人工智能(AI)在制药行业 中的应用。此外，OpenAI周一在社交媒体X平台上宣布，已收购医疗科技初创公司Torch。值得一提的 是，国内AI医疗应用亦呈现加速发展态势，蚂蚁旗下AI医疗产品阿福月活用户已突破1500万，字节、 百度、京东、腾讯等互联网大厂相继布局。 据悉，2025年12月，艾迪康与华为云正式签署合作协议，标志着双方在智慧医疗领域的协同创新步入全 新阶段。艾迪康与华为云此次携手合作，共同开启了以AI技术为引擎的智慧医疗新篇章。此次合作不 仅是技术能力与行业场景的深度融合，更是医学检验服务从传统模式向智能化、生态化演进的重要里程 碑。 ...

Core Insights - The article highlights a significant shift in the Chinese large model industry, with application projects accounting for nearly 60% of the market, indicating a transition from technical competition to value validation in commercial scenarios [1][3][25] - In 2025, the number of large model-related bidding projects reached 7,539, with a disclosed amount of 29.52 billion yuan, marking a dramatic increase of 396% and 356% compared to 2024 [1][3] - The report emphasizes the importance of industry-specific knowledge and high-quality private data as key competitive advantages in the evolving market landscape [19][20] Market Trends - Application projects dominated the bidding landscape, comprising 58% of the total projects, with a peak of 63% in November 2025 [1][5] - The trend shows a quarterly increase in application project share from 44% in Q1 to 61% in Q3, stabilizing at 60.5% in Q4 [5] - The highest monetary share came from computing projects at 52.9%, but their quantity share was only 27%, indicating a preference for direct procurement of computing power and existing models for application development [5] Industry Distribution - The top five industries by project quantity were education, government, telecommunications, energy, and finance, with the government sector leading in monetary share at approximately 40% [5] - The financial sector showed a notable shift from computing investment to application deployment in the latter half of 2025 [5] Vendor Landscape - Major players in the bidding market included general large model vendors like iFlytek, Baidu, Volcano Engine, and Alibaba Cloud, alongside specialized vendors like Zhongguancun KJ, which focused on niche markets [6][11] - Zhongguancun KJ ranked fourth among financial industry large model vendors, showcasing its deep industry expertise and successful project implementations [13] Case Studies - Zhongguancun KJ's collaboration with China Shipbuilding Group led to the development of a large model for the shipbuilding industry, integrating a vast knowledge base and enhancing operational efficiency [11][12] - In the finance sector, Zhongguancun KJ has served over 500 leading financial institutions, creating a comprehensive financial intelligent agent matrix that integrates AI capabilities into core business processes [13][14] Future Outlook - The market is expected to enter a "deep water zone" in 2026, where return on investment (ROI) will become a critical metric for evaluating AI projects [18] - The relationship between specialized vendors and general platforms is anticipated to evolve from competition to collaboration, fostering a symbiotic ecosystem [22][23]

在物资保障方面，新希望集团敞开棉兰分公司仓库，作为救援物资中转点。来自会员企业的大米、方便 面、雨具等物资在此集中整理，工作人员24小时轮班分拣、装车，随后分赴北苏门答腊和亚齐多地。 图为交接 仪式现场。 中新社记者 李志全 摄 仪式上，双方代表完成捐赠牌交接。印尼红十字会方面对印度尼西亚中国商会总会及在印中资企业在灾 害发生后提供的支持表示感谢，并表示相关善款将用于受灾地区应急救援、民众安置及灾后恢复等工 作。 2025年年底，印尼苏门答腊岛多地遭遇持续强降雨，引发严重洪涝灾害，部分地区道路中断、电力受 损、通信失联，民众生产生活秩序受到影响。灾情发生后，印度尼西亚中国商会总会迅速组织会员企业 开展联合行动，联动多方力量开展救援。166家中资企业参与捐赠，累计募集善款约77亿印尼盾，由印 尼红十字会统一接收并用于灾区救援。 据介绍，洪水阻断交通后，北苏门答腊巴塘水电站一度成为"孤岛"，约400名中外员工被困，断水断 电，粮食告急。中国石油印尼公司紧急从油田基地调配1.2万升柴油支援灾区。当发电机重新启动，避 难场所恢复供电，也为周边受灾村落的临时救援点提供了能源保障。 中新网雅加达1月10日电 (记者 李志 ...