2025.09.29 本文字数：2124，阅读时长大约4分钟 作者 |第一财经 李娜 尽管资本市场对算力泡沫发出的警告不断，但英伟达CEO黄仁勋依然对算力产业的发展调高了预期。在 近期一次访谈中，他预测AI推理即将迎来十亿倍的增长，并指出由AI增强的经济活动将催生一个每年5 万亿美元的AI基础设施资本支出市场。 值得注意的，就在访谈前的72小时，英伟达与OpenAI正式达成战略合作，黄仁勋称这笔交易为"能想象 到的最聪明的投资之一"。但也有券商分析师将这种交易模式比喻为金庸小说中的"梯云纵"——看似向 OpenAI投资1000亿美元，实则这些资金又以订单形式流回自家口袋。这种左脚踩右脚的模式，使英伟 达提前锁定利润。 面对这样的"算力激进者"，比起泡沫更担心的是错过，近一个月以来，如甲骨文、英特尔等厂商开始以 订单、资金或股权方式与英伟达结盟，一个以美国企业主导的AI新生态正在酝酿。而在国内算力市场 上，随着单颗算力芯片的焦虑逐步缓解，建立一个具有同样生命力和吸引力的生态系统也开始变得迫 切。 生态竞争进入拐点 不断被抬高的需求正在驱动全球算力竞赛进入淘汰赛阶段。 在英伟达与OpenAI的合作中，计划建设高达 ...

对于国内算力市场，建立自己的生态系统也开始变得迫切。 尽管资本市场对算力泡沫发出的警告不断，但英伟达CEO黄仁勋依然对算力产业的发展调高了预期。在 近期一次访谈中，他预测AI推理即将迎来十亿倍的增长，并指出由AI增强的经济活动将催生一个每年5 万亿美元的AI基础设施资本支出市场。 值得注意的，就在访谈前的72小时，英伟达与OpenAI正式达成战略合作，黄仁勋称这笔交易为"能想象 到的最聪明的投资之一"。但也有券商分析师将这种交易模式比喻为金庸小说中的"梯云纵"——看似向 OpenAI投资1000亿美元，实则这些资金又以订单形式流回自家口袋。这种左脚踩右脚的模式，使英伟 达提前锁定利润。 面对这样的"算力激进者"，比起泡沫更担心的是错过，近一个月以来，如甲骨文、英特尔等厂商开始以 订单、资金或股权方式与英伟达结盟，一个以美国企业主导的AI新生态正在酝酿。而在国内算力市场 上，随着单颗算力芯片的焦虑逐步缓解，建立一个具有同样生命力和吸引力的生态系统也开始变得迫 切。 生态竞争进入拐点 不断被抬高的需求正在驱动全球算力竞赛进入淘汰赛阶段。 这一决策也意味着华为主动斩断了一条可能的"利润路径"，为了获得互联网等企业的 ...

Core Viewpoint - Computing power is the engine of the digital economy, becoming a core resource in the intelligent transformation of society, especially with the rise of AI models [1] Group 1: Current State of Computing Power in China - As of June 2023, China's total number of operational computing power centers reached 10.85 million standard racks, with intelligent computing power at 788 EFlops, ranking among the top globally [1] - The rapid iteration of AI raises concerns about insufficient computing power [1] Group 2: Huawei's Strategy - Huawei is adopting a differentiated path by constructing a new computing supply system based on "super nodes + clusters" to address the increasing demand for computing power and external limitations in chip manufacturing [2] - The "super node" concept integrates computing chip resources to create a low-latency, high-bandwidth computing entity, enhancing computing efficiency for training and inference of large models [2] - Huawei's latest super node products, Atlas 950 SuperPoD and Atlas 960 SuperPoD, support 8,192 and 15,488 Ascend cards respectively, with the computing power scale of the new clusters exceeding 500,000 and reaching 1 million cards [3] Group 3: Future Outlook and Innovations - Huawei aims to innovate systematically with the "super node + cluster" approach, providing sustainable and scalable computing power for China's AI development [3] - The company plans to advance its computing capabilities at a pace of nearly one generation per year, doubling the computing power each time [3] - Huawei has introduced the UnifiedBus protocol to overcome technical bottlenecks in large-scale super node interconnection, promoting an open ecosystem for computing power [5][6] Group 4: Open Source and Ecosystem Development - Huawei is committed to open-sourcing its Ascend hardware to accelerate developer innovation and build a robust ecosystem [6] - The trend towards open-source technology is seen as essential for the construction of a computing ecosystem, with significant implications for reducing computing costs and fostering comprehensive system innovation [6][7] - Recent government policies are aimed at strengthening the open-source landscape, providing a supportive environment for the development of the computing ecosystem in China [7]

Core Viewpoint - Huawei is significantly enhancing its ecosystem strategy by investing in open-source technologies, talent development, and global collaboration, aiming to create a comprehensive platform that supports developers and fosters innovation in the intelligent era [4][5][12]. Group 1: Open-Source and Ecosystem Development - The release of OpenHarmony 6.0 supports various devices and has attracted over 9,200 contributors, contributing more than 130 million lines of code [3][7]. - Huawei plans to invest 15 billion RMB annually over the next five years to support ecosystem development and engage 15,000 people in platform development [4][5]. - The company emphasizes the importance of open-source projects like OpenHarmony, openEuler, and openGauss, which have rapidly evolved and become key components of Huawei's ecosystem [12][15]. Group 2: AI and Computing Platforms - Huawei announced the "Tian Gong Plan," committing 1 billion RMB to support AI ecosystem innovation, aiming to incubate over 10,000 AI-native services and 5,000 intelligent agents [8]. - The Kunpeng and Ascend platforms provide essential computing capabilities, with significant upgrades planned for both, enhancing performance and efficiency in various industries [8][9]. - Huawei's cloud services have seen a growth of approximately 2 million developers in the past year, totaling 8.5 million, positioning the cloud as a critical bridge for developers [9][10]. Group 3: Talent and Global Collaboration - Huawei is launching the "Basic Software Thousand Schools Initiative," targeting over 2,000 universities globally to train 1 million new software talents [14]. - The company actively collaborates with international open-source foundations and standard organizations to enhance its global influence and provide a stable environment for partners [14][15]. - Huawei's strategy focuses on creating a "global developer community," which serves as a platform for technology exchange and innovation, aiming to lower barriers for developers [15].

Core Viewpoint - Huawei is leading the development of an open and shared AI computing ecosystem through its innovative supernode architecture, which aims to create an "AI highway" that benefits various industries and players of all sizes [1][2][26]. Group 1: Supernode Technology - Huawei unveiled the supernode architecture at the Huawei Connect conference, introducing a range of supernode products that cover all scenarios from data centers to workstations [3]. - The Atlas 950 SuperPoD is designed for large-scale AI computing tasks, featuring innovations in system-level design, including zero-cable interconnect and enhanced cooling reliability [4]. - Compared to NVIDIA's upcoming products, the Atlas 950 supernode shows significant advantages in scale, total computing power, memory capacity, and interconnect bandwidth, achieving 56.8 times, 6.7 times, 15 times (1152TB), and 62 times (16.3PB/s) respectively [5]. Group 2: Open Source and Collaboration - Huawei is fully opening its supernode technology to the industry, allowing for shared technological benefits and collaborative innovation [16]. - The company is also opening its hardware components, including NPU modules and AI cards, to facilitate incremental development by customers and partners [18]. - On the software side, Huawei is making its operating system components open source, enabling users to integrate and maintain versions according to their needs [20]. Group 3: Industry Impact and Ecosystem - The supernode technology is designed to serve various industries, including internet, finance, telecommunications, and manufacturing, enhancing computing efficiency and business capabilities [29]. - The UnifiedBus protocol enables high bandwidth and low latency interconnectivity among computing and storage units, addressing traditional cluster reliability issues [33]. - Huawei's approach fosters an open ecosystem where different hardware manufacturers and software developers can collaborate, breaking down barriers in the AI computing landscape [42]. Group 4: Future Prospects - The Atlas 950 SuperCluster is set to be 2.5 times larger and 1.3 times more powerful than the current largest global cluster, xAI Colossus, positioning Huawei as a leader in computing power [48]. - By promoting an open and collaborative AI computing environment, Huawei aims to establish a sustainable and secure foundation for the AI industry in China, potentially leading to a new cycle of innovation [52][53].

Core Insights - Huawei plans to invest 150 billion RMB annually for ecosystem development over the next five years, along with 1500P of open-source community computing power and 15,000 personnel for ecosystem platform development and support [1][6] Group 1: Ecosystem Development - Huawei's industrial layout is deepening and expanding, moving from a focus on connectivity to include terminal and computing ecosystems, targeting not only ToB and ToC customers but also ToD developers [1] - The company emphasizes "four commitments": open-source openness, talent development, global cooperation, and strategic investment [1][6] Group 2: Open Source Initiatives - In the operating system domain, OpenHarmony has gathered over 9,200 community contributors, contributing 130 million lines of code and supporting over 1,300 software and hardware products [2] - Huawei has open-sourced its entire Kunpeng software series, including openEuler OS and openGauss database, enhancing its offerings in general computing [2] Group 3: AI and Computing Innovations - Huawei's Ascend software is fully open-sourced, with new open-source projects like CANN and Mind series being introduced, supporting mainstream open-source communities [2] - The company has developed low-density computing formats that significantly reduce memory usage and enhance matrix multiplication performance, which will be shared with the global computing alliance [3] Group 4: Talent Development - Huawei collaborates with global universities to develop over 3,000 courses and establish more than 3,000 ICT academies, training over 1.7 million talents [4] - The company has launched the "Basic Software Thousand Schools Initiative" to train 10,000 teachers and 1 million new software talents across 20+ countries [4] Group 5: Global Cooperation - Huawei is enhancing its cooperation with various open-source foundations and communities, providing end-to-end resources and support to empower global developers [6]

Core Insights - The core viewpoint presented by the director of Fudan University's AI Innovation and Industry Research Institute is that the development of artificial intelligence (AI) is characterized by three main trends: open-source openness, value delivery, and safety and trustworthiness [1][5]. Group 1: Open-Source Openness - The most significant change in the AI field by 2025 is the transition of "open-source openness" from a concept to reality, reshaping the entire industry ecosystem [1]. - The emergence of "DeepSeek" has transformed the generative AI landscape, achieving "tenfold growth and efficiency improvement" through its open-source architecture and powerful capabilities [1]. - Major players in the industry, such as OpenAI, are recognizing the value of open-source, as evidenced by their first open-source release in six years, indicating a shift in industry perspective [1]. Group 2: Value Delivery - AI is evolving from "selling tools" to "selling results," transitioning from auxiliary tools to deliverable value systems like "Copilot" and "Auto Pilot," which rely on deep integration with industry-specific knowledge [1]. - In the medical field, the "Renewal Intelligent Agent" has been implemented at Zhongshan Hospital, showcasing the advantages of deeper contextual understanding and higher quality data, enabling comprehensive interpretation of multimodal data [2]. Group 3: Safety and Trustworthiness - Safety and trustworthiness are emphasized as the foundational requirements for AI development, with concerns about issues like "fabrication" and "hallucination" in large models [2]. - The accuracy of models in the medical field is notably low, with some achieving only 55% accuracy, raising significant concerns [2]. - Several risk cases highlight the challenges of distinguishing between true and false information, such as AI-generated doctoral theses and deepfake scams [2]. - Key technological pathways proposed to enhance safety include explainable AI, retrieval-augmented generation (RAG) combined with neural-symbolic systems, high-quality data governance, adversarial techniques, and self-awareness in models [3][4][5].

Core Insights - Huawei showcased breakthroughs in general computing, large model technology, and AI applications at the "2025 Huawei Computing Scenario Release Conference" [1] - The launch of the "xPN Pioneer Action" indicates Huawei's commitment to support partners in driving digital transformation across various industries [1] Open Source Strategy - Huawei announced the full open-source of CANN (Compute Architecture for Neural Networks) and Mind series application tools, enabling developers to innovate more effectively [3][4] - The open-source strategy aims to expand the ecosystem and accelerate the AI industry's development by allowing partners to access foundational frameworks for performance tuning and toolchain development [6] Product Development and Ecosystem - Huawei's Ascend components and solutions cover all AI scenarios, with a focus on enhancing product competitiveness and ecosystem richness by 2025 [4] - The number of Ascend partners is expected to exceed 100 by 2025, with over 100 products developed, while the Kunpeng partner program will also see similar growth [8] Market Support and Collaboration - Huawei is investing 8 million to support partners in expanding their business, providing comprehensive assistance in research, marketing, and supply chain management [10] - The company aims for a 350% growth in the xPN partner business by 2025, driven by customer demand and support capabilities [12] Future Outlook - Huawei plans to enhance its product matrix and cover a wide range of computing scenarios, focusing on low to high computing power solutions [12] - The strategy emphasizes collaboration with partners to ensure that the benefits of computing power are accessible across various industries [13]

Core Insights - ChatGPT-5 was launched on August 8, 2025, but was quickly criticized for slow response times and frequent errors, leading to the reintroduction of GPT-4o by OpenAI [1] - The AI industry is facing two major challenges: data exhaustion and computational cost limitations [1] - China is addressing these challenges through open-source initiatives and algorithm innovations, positioning itself as a key player in the AI landscape [1][2] Group 1: Current AI Development Challenges - The latest AI model, GPT-5, has been criticized for its slow response and frequent errors, raising questions about the effectiveness of generative AI algorithms [10] - AI systems, particularly deep learning models, require significant computational power, with Nvidia's H100 chips consuming up to 700W each, leading to concerns about energy consumption [11] - The depletion of high-quality training data is forcing a reevaluation of current pre-training methods for AI models [12] Group 2: China's AI Advantages and Contributions - China is leveraging open-source models like DeepSeek-V3, which has a training cost of less than $6 million, to drive global AI accessibility [24] - The country is actively integrating AI into its real economy, focusing on innovative production models and large-scale replication [1][24] - Chinese companies are increasingly becoming key players in the AI landscape, with a focus on collaboration and technological breakthroughs [24][32] Group 3: Future Trends in AI Development - The AI revolution is being driven by algorithm innovations, autonomous chips, and application scenarios, with China leading the charge [6] - The emergence of photonic and quantum chips is expected to significantly enhance AI computational capabilities [40][43] - The trend towards open-source AI models is seen as a necessary evolution for the industry, promoting collaboration and innovation [20][24] Group 4: AI Application Areas - The automotive industry is a primary battleground for AI applications, particularly in autonomous driving technology [51][52] - Humanoid robots are increasingly integrating AI technology, with a growing number of companies involved in this sector [55] - AI agents are expected to play a crucial role in various sectors, enhancing decision-making and operational efficiency [57][58] Group 5: Global AI Governance and Cooperation - China is advocating for global cooperation in AI governance, emphasizing the need for a shared ethical framework [63][66] - The country has been proactive in establishing international agreements and frameworks for AI safety and governance [67] - The focus on collaborative efforts in AI development is seen as essential for ensuring the technology aligns with human values and long-term interests [66][68]

Core Insights - The 2025 Open Computing Technology Conference held in Beijing focuses on the development trends of MoE large models and AI agents, emphasizing the importance of open computing in enhancing both vertical scaling and horizontal efficiency [1] - Open-source large models are reshaping the global AI industry landscape, significantly lowering the barriers for enterprises and individual developers to access advanced AI capabilities, thus accelerating the shift from closed to open collaboration [3] - The rise of open computing is fostering tighter collaboration within the data center industry chain, which is crucial for the rapidly evolving AI sector [4] Industry Developments - The MoE large models are experiencing rapid growth in parameter counts, necessitating innovations in computing architecture to meet the extreme demands for computing density and interconnect speed [4] - The power requirements for AI data centers are projected to escalate from over 100 kW per cabinet to above 1 MW, indicating a shift towards GW-level power demands [4] - China has a significant advantage in energy infrastructure, particularly in renewable energy, with 90% of new installations in Q1 2025 coming from renewable sources, contributing to 35.9% of the total power generation [5] Collaborative Efforts - The establishment of the "GW-level Open Intelligent Computing Center OCP China Community Group" aims to leverage China's strengths in energy and computing infrastructure to promote the implementation of AI open system strategies [5] - OCP is actively collaborating with OCTC to explore the deployment of advanced AI infrastructure technologies and research outcomes in the Chinese market [5] - Future initiatives will focus on creating a global open-source coalition to enhance collaboration among developers across different countries and regions, promoting innovation and integration within the global supply chain [6]