Core Viewpoint - The theme of the "2025 China Mobile Global Partner Conference" is "Carbon-Silicon Symbiosis and Co-creation in the AI+ Era," emphasizing the integration of AI technology and economic benefits to drive this trend forward [2][13]. Group 1: AI and Carbon-Silicon Symbiosis - China Mobile plans to double its overall investment in artificial intelligence by the end of 2028, indicating a strong commitment to AI development [2][13]. - The company aims to explore the construction of a 100,000-card intelligent computing cluster, targeting a national intelligent computing scale exceeding 100 EFLOPS [13][14]. - The integration of AI with various sectors is expected to enhance the efficiency and capabilities of smart terminals, smart connected vehicles, and intelligent robots, with a goal of exceeding ten million units shipped [18][19]. Group 2: Robotics and Industry Trends - The robotics industry in China is experiencing rapid growth, with significant technological advancements observed globally [5]. - Challenges remain in both household and industrial applications of robotics, particularly in achieving higher efficiency and lower costs compared to human labor [5][12]. - A notable collaboration between Yushu Technology and Zhiyuan Robotics resulted in a 124 million yuan order from China Mobile, highlighting the commercial potential in the robotics sector [9]. Group 3: Strategic Partnerships and Collaborations - Major partners of China Mobile, including Huawei, ZTE, Intel, and Alibaba, showcased their latest technologies and solutions at the conference, indicating a robust ecosystem of collaboration [3][15]. - Intel and China Mobile's partnership aims to enhance sports viewing experiences through AI-driven technologies, showcasing the integration of content and hardware [22][23]. - The conference highlighted the importance of continuous collaboration with industry partners to drive the development of "5G+" technologies, with over 2.65 million 5G base stations already established [25].

Core Insights - Chinese AI startups are rapidly capturing global market share with innovative products like smart recording devices and AI toys, while also expanding into overseas markets with technologies like Robotaxi [1][4]. Industry Overview - The efficiency of China's manufacturing supply chain, rapid AI iteration, and keen product awareness are driving competitive advantages for domestic companies [2][6]. - The AI hardware sector is experiencing a wave of innovation, with companies like Plaud.AI achieving significant sales milestones and funding rounds for AI toy startups [3][5]. Market Dynamics - The emergence of AI hardware is not just a product innovation race but a transformation of the industrial paradigm, shifting from "cost-effectiveness" to "intelligence" [5][7]. - Chinese companies are leveraging their technological capabilities to redefine standards in new hardware, moving beyond simple manufacturing to creating advanced solutions [4][6]. Technological Advancements - The integration of AI and manufacturing is leading to a new generation of AI hardware products, supported by a robust domestic supply chain that enhances product development speed and market responsiveness [6][7]. - The domestic AI chip industry is witnessing significant growth, with several companies preparing for IPOs and reporting substantial business orders, indicating a shift from experimental products to commercially viable solutions [8][11]. Ecosystem Collaboration - The collaboration among various stakeholders in the AI ecosystem is crucial for overcoming challenges in computing power and establishing a unified architecture for AI applications [14][16]. - Companies are focusing on building open systems and protocols to enhance interoperability and efficiency in AI computing, which is essential for scaling operations [15][16]. Future Outlook - The convergence of capital investment and technological breakthroughs is expected to solidify China's position in the global AI landscape, transitioning from a follower to a leader in AI innovation [17][18].

从"单点突破"到"系统攻坚"，大模型跨越式发展的条件正日趋成熟。DeepSeek-R2酝酿之际，其团队已 在论文中阐述下一代人工智能系统的创新蓝图——"模型+硬件"的协同优化设计，意味着大模型发展不 再单纯依靠算力堆砌或算法单一创新，而是软硬件并行研发的"集团军作战"。当下，像华为昇腾384超 节点、上海AILab系统平台的相关突破，都为大模型新发展筑牢了基础，也让我们坚信下一代人工智能 系统的推出只是时间问题。 互联网思维碰上人工智能时代，"流量焦虑""爆款心态"已成创新枷锁。在这个算力成本高昂、技术迭代 迅速、计算量极大的时代，急功近利的冒进易引发系统性风险。唯有摒弃短视观念，专注技术深耕与生 态共建，才能在这场关乎国家竞争力的科技竞赛中取得最终胜利。 但大模型竞争截然不同。这是硬科技的角力场，技术指标和模型性能是实打实的，即使用户数多，如果 性能不过硬，也会在技术竞争浪潮中掉队。以DeepSeek-R1为例，其发布之初使用率的飙增，根源在于 算法架构的创新与训练数据的深度优化，而非依赖用户规模。大模型的价值如同精密仪器，参数精度、 响应速度、多模态能力等硬指标才是衡量其竞争力的核心要素。 从"流量垄断" ...

Group 1 - The core viewpoint is that the artificial intelligence (AI) industry is expected to continue its development trend and market performance, with specific sectors such as smart cities, smart transportation, smart healthcare, smart education, low-altitude economy, AI+ finance, and AI+ energy likely to benefit first [1][2] - In July, the AI sector index (884201.WI) increased by 5.37%, outperforming the Shanghai Composite Index, which rose by 3.74%, and the CSI 300, which rose by 3.54%. The ChiNext Index saw an increase of 8.14%. The trading volume for the AI sector reached 1.366 trillion yuan, a month-on-month increase of 38.81% [1] - The "Artificial Intelligence+" action plan was approved, aiming to accelerate the commercialization of AI applications and leverage China's complete industrial system, large market scale, and rich application scenarios [2] Group 2 - Huawei's Ascend 384 SuperNode was showcased at the 2025 World Artificial Intelligence Conference (WAIC), marking a turning point for domestic computing power. This system consists of 16 units, with 12 for computing and 4 for communication, achieving low-latency interconnection through a high-speed bus [3] - The Ascend 384 SuperNode's bus technology addresses communication bottlenecks within the cluster, providing new insights for the development of domestic computing power and narrowing the gap with chip giants like NVIDIA [3]

Core Viewpoint - The incident surrounding Nvidia's H20 chip highlights the dependency risks in China's core technology sectors and may accelerate the domestic chip industry's push for self-innovation [2][7]. Group 1: Nvidia's H20 Chip Situation - Nvidia's H20 chip, designed for AI acceleration in compliance with U.S. export restrictions, has faced significant challenges in the Chinese market, including a ban that resulted in over $1 billion in quarterly revenue loss [3][4]. - Following the approval of export licenses by the U.S. government, Nvidia's stock saw a brief uptick, but the subsequent security concerns led to renewed scrutiny from China's internet regulator [4][5]. - Nvidia has firmly denied the existence of backdoors or monitoring software in its chips, emphasizing the importance of building trustworthy systems [5][6]. Group 2: Domestic Industry Response - The H20 chip's security issues have prompted domestic companies to increase their testing and application of local chip alternatives, recognizing the importance of self-reliance in core technologies [7][9]. - Domestic chip manufacturers are rapidly developing competitive alternatives, with notable advancements in performance and capabilities [8][9]. - The incident has created a significant opportunity for domestic GPU solutions in data centers and AI training, potentially reshaping the market landscape [9].

Core Insights - The key challenge for companies in leveraging AI capabilities lies in effectively utilizing computing power rather than merely possessing it, with a growing demand for specialized, value-driven computing services [2][4] - The recent WAIC highlighted a significant transformation in the industry, with a more complete supply chain and an explosion of vertical models, indicating a restructuring of the computing service market [2][4] Group 1: Market Dynamics - The computing service market is characterized by a "demand-driven" nature, where businesses are increasingly measuring computing value based on business outcomes rather than raw performance metrics like FLOPS [3][7] - The release of ChatGPT in late 2022 triggered a global AI boom, leading to a tenfold increase in computing demand as major companies initiated large model projects, while supply constraints and chip bans exacerbated the market's supply-demand imbalance [4][6] Group 2: Value Creation - Pure computing power does not generate value; it must be complemented by service layers that enhance usability and efficiency, transforming raw computing into effective AI productivity [5][6] - Companies are shifting their focus from merely having usable computing power to seeking high-quality, efficient computing services that meet their specific business needs [5][6] Group 3: Cost and Quality Assessment - Companies often misjudge computing costs by assuming 100% utilization rates, while actual usage can be significantly lower, leading to a substantial discrepancy in cost assessments [6][7] - There is a prevalent issue of resource misallocation, where financially strong companies hoard high-end chips for simple tasks, while those with limited budgets opt for low-performance computing, ultimately hindering operational efficiency [6][7] Group 4: Service Models - The emergence of "expert services" in the computing service market aims to align computing resources with actual business needs, emphasizing the importance of accurate resource selection and architecture design [7][8] - After resource selection, companies require reliable foundational services, including real-time monitoring and data analysis, to optimize performance and address issues promptly [8][9] Group 5: Hybrid Solutions - Companies are encouraged to consider hybrid cloud solutions, where they can maintain a basic level of computing for daily operations and leverage public cloud resources for unexpected demands, thus optimizing costs [9]

Core Insights - The rapid development of China's computing power industry is highlighted by significant advancements in infrastructure and technology, with a focus on high-quality development and strategic initiatives like the "East Data West Computing" project [1][4][9] - The demand for intelligent computing (智算) is surging, with its scale reaching 748 EFlops, accounting for 35% of the total computing power in China, and projected to grow to 1037.3 EFlops by 2025 [2][3] - The integration of computing resources across the nation is being prioritized to enhance accessibility and efficiency, with initiatives like the establishment of a national computing network and the "Computing Power Internet" [4][5][7] Industry Developments - The computing power infrastructure in China is expanding, with over 1,043 million standard computing racks in use, marking an 18.5% increase from 2024 [2] - Major telecom companies are enhancing their computing capabilities, with China Telecom's central computing center in Wuhan expanding by 2 EFlops to support AI applications [3] - The "East Data West Computing" initiative has seen the total computing power of eight major hubs reach 215.5 EFlops, with intelligent computing accounting for 80.8% of this total [3] Technological Advancements - The introduction of advanced technologies, such as liquid cooling, is significantly improving energy efficiency in data centers, with reductions in energy consumption by 50%-60% [8] - The deployment of high-capacity optical transmission networks is facilitating efficient computing resource allocation, with companies like China Mobile and China Unicom achieving significant advancements in network capabilities [6][7] Policy and Strategic Initiatives - The Chinese government is actively promoting policies to drive the integration of computing power and energy efficiency, aiming for a PUE value below 1.35 in existing data centers by 2027 [8] - The establishment of a national computing network and the "Computing Power Internet" is expected to enhance the efficiency of resource allocation and support over 7,000 computing entities in meeting demand [4][5]

Core Insights - Huawei's Ascend 384 supernode has made its debut, achieving a computing power of 300 Pflops through self-developed Matrix-Link technology, positioning it as a competitor to NVIDIA's latest GB200 NVL72 [1] - Domestic AI chip manufacturers are collaborating to build a robust ecosystem, with significant advancements showcased at the World Artificial Intelligence Conference [2] - The performance of domestic AI chip companies has surged, with notable revenue increases reported across the sector [2][3] Group 1: Huawei and Its Innovations - Huawei's Ascend 384 supernode has been recognized as a "treasure of the exhibition" at the World Artificial Intelligence Conference, attracting significant attention [1] - The supernode's architecture allows 384 cards to operate as a single computer, showcasing its advanced capabilities [1] - The deployment of Huawei's technology is already in multiple data centers across the country, providing services to various sectors including internet and automotive [2] Group 2: Domestic AI Chip Developments - Companies like Nucypher and Suirun Technology are developing advanced chips, with the C600 model set for small-scale production in Q4 of this year [1] - The domestic AI chip industry is experiencing rapid growth, with companies like Moore Threads reporting a 256% increase in revenue, driven by AI computing business [2] - Cambrian Technology has turned a profit for the first time in years, with a 40-fold increase in revenue and over 2-fold profit growth in Q1 of this year [3] Group 3: Industry Trends and Collaborations - The domestic AI chip industry is moving towards a trend of adopting local chips, with significant collaborations among companies like Xizhi Technology and ZTE [2] - The introduction of light-interconnected GPU supernodes is expected to reduce power consumption and latency significantly [2] - The overall performance of domestic AI chips has led to a substantial increase in market presence, indicating a shift away from reliance on foreign technology [3]

Core Insights - The 2025 WAIC has seen unprecedented interest, highlighting the rapid evolution of the domestic large model industry since 2025, characterized by three major trends: the rise of reasoning models as a new technological high ground, the transition from conceptual applications to practical implementations, and significant breakthroughs in domestic computing power [2][29]. Group 1: Industry Trends - The competition landscape of large models is shifting from chaotic "hundred model battles" to a more rational and intense "midfield battle," with a focus on reasoning models [2][29]. - The number of companies in the robotics industry at WAIC 2025 surged from 18 in 2024 to 80, indicating a growing interest and investment in this sector [4]. - Major players are no longer solely competing on model parameters but are showcasing diverse application ecosystems, emphasizing the importance of industrial ecology, business models, and international competitiveness [5][29]. Group 2: Technological Developments - The emergence of reasoning models marks a qualitative leap from basic capabilities to advanced cognitive functions, with DeepSeek-R1's launch being a pivotal event [6][7]. - Since the release of DeepSeek-R1 in January 2025, numerous leading firms have introduced their own reasoning models, indicating a rapid technological advancement [8]. - The competition now emphasizes model architecture, reasoning mechanisms, and parameter strategies, with a shift towards hybrid architectures to meet performance demands [10][14]. Group 3: Application and Market Dynamics - The transition from technology demonstration to practical application is evident, with companies focusing on B-end and C-end strategies [15][22]. - Companies like Tencent and Alibaba are leveraging their platforms to enhance user experience, while smaller firms are concentrating on B-end capabilities [15][18]. - The integration of large models into various industries, such as finance and healthcare, is accelerating, showcasing their practical utility [22][23]. Group 4: Domestic Computing Power - Domestic computing power is gaining momentum, with Huawei's Ascend 384 super node showcasing significant advancements in AI chip technology [24][25]. - The rapid increase in daily token usage by companies like Alibaba and ByteDance highlights the growing demand for computing resources [24]. - The establishment of the "MoXin Ecological Innovation Alliance" reflects a trend towards collaborative development among domestic chip and infrastructure manufacturers [27]. Group 5: Future Outlook - The large model industry is entering a phase of refinement, focusing on core technologies, key applications, and building ecological moats [30]. - Future trends indicate that reasoning models will evolve towards multimodal reasoning and embodied intelligence, while domestic computing power will shift from a catch-up mode to a competitive mode [30].

Group 1: Core Insights - The emergence of Huawei's Ascend 384 Super Pod signifies a potential shift towards domestic computing power in China, indicating that the era of domestic computing capabilities may have arrived [1][2] - The breakthroughs in single-chip computing power and large-scale cluster technology have been achieved, with notable advancements from companies like Huawei and Muxi [2][3] Group 2: Domestic Computing Power Developments - Huawei's Ascend 384 Super Pod features a total computing power of 300 PFlops, surpassing NVIDIA's similar system, which has a total computing power of 180 PFlops, making Huawei's performance 1.7 times greater [3] - The Ascend 384 Super Pod consists of 12 computing cabinets and 4 bus cabinets, achieving the industry's largest scale of 384-card high-speed bus interconnection, enhancing data transmission efficiency [2][3] - Other companies, such as Muxi and Hengwei Technology, are also making significant strides in the domestic computing power sector, with Muxi's new GPU product and Hengwei's TPU architecture [4][5] Group 3: International Expansion of Domestic Computing Power - The Chinese government emphasizes that artificial intelligence can be an international public good, promoting technology sharing to bridge global intelligence gaps, particularly for developing countries [8] - Companies like Feiteng are actively pursuing international markets, with plans to embed domestic chips into overseas infrastructure projects [7][8] Group 4: Advantages of Domestic Computing Power Going Global - The full-stack solution capability of Chinese computing power is maturing, allowing for the establishment of a replicable technology ecosystem that includes algorithm optimization and talent training [10] - China's complete industrial chain in AI provides a competitive edge in deploying solutions across various sectors, including consumer and business applications [11] Group 5: Significance of the Global Expansion of Domestic Computing Power - The global expansion of domestic computing power reduces reliance on Western technologies and demonstrates that domestic technologies can compete internationally [12] - The promotion of China's AI ethical framework as a potential international standard could reshape global governance in AI [12] - The initiative to build offshore data resource pools can enhance domestic model training by providing diverse data sources [14]