2026.3.2本周早盘 1周末重要新闻 ①伊朗遇袭，美以轰炸伊朗在首都及周边地区，伊朗最高领袖及多位军方高层遇害。 伊朗方面对美以也有回击。 ②美军此次针对哈梅内伊的斩首行动，代号"沉默圣城"，仅出动1架MQ-9B"海上卫士"无人机、1支8人特种部队先 遣队，核心作战力量是Claude 3Opus大模型+Palantir Foundry国防平台的AI组合，以及接入CE 2026.3.2本周早盘 1周末重要新闻 ①伊朗遇袭，美以轰炸伊朗在首都及周边地区，伊朗最高领袖及多位军方高层遇害。 伊朗方面对美以也有回击。 2本周节奏 ①首先有色原油化工农产品等大宗肯定会高开，但受美元走强，战争持续周期不长的预期影响，很可能变成兑现 点位，在车上的可做t，没上车的最好不要追高。 摩根连续吹高黄金，高盛看空铜，有色的朋友可以适当减仓。 ②石油石化的板块，强的那些个标的，洲际油气，山东墨龙肯定一字板，前排买不到的别上后排，紧盯下国际期 货，最好开盘看获利盘兑现完再考虑是否上车etf。 ③小金属和化工这里则是独立逻辑，和需求端有关，和涨价线有关，不是主跟的避险逻辑，尤其是最近走的最强 的钨，其次是锗，镓，磷化铟等，化工材料可以 ...

一、行情 2月27日，华为产业链大涨，华胜天成2连板，格尔软件、新炬网络、拓维信息等多股涨停。 二、事件：华为发布AI新产品，DeepSeek有望率先适配华为芯片 1）2月26日，华为云码道公测版正式发布，提供集代码大模型、IDE、自主开发模式于一体的智能编码解决方案，覆盖多类AI Coding技术，接入GLM-5.0、 DeepSeek-V3.2及华为自研模型，含鸿蒙专属模型。（智通财经） 2）26日，DeepSeekV4Lite模型测试效果大幅提升，支持1M上下文+原生多模态，首批SVG示例传播广泛，目前正由华为等芯片厂商测试。（智东西） 三、机构解读 1）AI编程重塑核心生产力方式，大模型核心技术赋能编程工具。基于大模型的自动化编程与代码生成，AICoding提升软件开发效率与自动化水平。 AI编程的价值集中在：一是提升软件开发的效率和质量；二是降低技术门槛；三是加速项目迭代等周期。大模型编程能力大幅跃进，核心技术赋能 AICoding工具。近年来国内外大模型在编程领域技术能力提升显著，其中Claude和GPT系列大模型在代码生成和部署排名领先，底层技术能力提升正推动AI 编程工具从Copilot（辅助 ...

| 表格 | | | | | | --- | --- | --- | --- | --- | | 年份 | 销售收入 | 同比 | 净利润 | 营业利润 | | 2019 | 8,588 | | 627 | 778 | | 2020 | 8,914 | +3.8% | 646 | 725 | | 2021 | 6,368 | -28.6% | 1,137 | 422 | | 2022 | 6,423 | +0.9% | રૂટર | 1,044 | | 2023 | 7,042 | +9.6% | 870 | 1,044 | | 2024 | 8,621 | +22.4% | ୧೭୧ | 794 | 股票频道更多独家策划、专家专栏，免费查阅>> 责任编辑：山上 梁华表示，2025年华为整体经营稳健，公司持续做强核心竞争力，战略聚焦；坚持走高质量发展道路，以质取胜；努力为全球客户提供有竞争力的产品和服 务。 目前，鸿蒙生态正在从可用走向好用，搭载HarmonyOS 5和HarmonyOS 6的终端设备数突破4000万，可获取的原生应用和云服务超过7.5万个，在金融、电 力、能源、交通、通信等行业也得到广泛的应用 ...

印度的这场AI峰会，翻车了。原本一个应该展示科技创新的舞台，硬生生被办成了一个政治站队秀，场面尴尬而失控。莫迪政府口口声声说要独立发展 AI，然而背后却是紧紧拥抱美国，显然并未考虑与中国展开任何合作。中国的AI发展路线，强调开源、低成本与普惠，恰恰最适合像印度这样的发展中国 家。单拿DeepSeek那款开源模型来说，印度如果采用，将大幅降低成本，甚至能解决因电网老化而频繁崩溃的问题，尤其是数据中心的绿色能源技术，对 印度来说，无疑是一个理想的解决方案。但即便如此，印度政府选择继续与美国巨头合作，甘愿付出巨额代价，让谷歌（150亿美元）、微软（175亿美元） 和亚马逊（350亿美元）来为印度建设数据中心。 在技术方面，印度并不傻，心里清楚什么是好的。就拿一个典型的例子来说，某些参展的印度大学，竟然把中国宇树科技的机器狗贴上自家研发的标签，公 开展示。明明知道中国的技术好，为什么不与中国合作呢？原因很简单，印度心里明白自己无法独立发展AI，只能站队。站对了队，科技的好坏就不再重 要，立场成了最重要的事。莫迪政府的算盘打得很好，但显然计算错了。 印度的玩法似乎挺精明。它意识到，自己根本无法在基础模型研发上与中美抗衡 ...

Core Viewpoint - The article argues that Elon Musk, with his vast wealth and influence, poses a significant challenge to China, more so than any U.S. president, due to his control over critical technologies and industries that could reshape global order [1][3]. Group 1: Musk's Wealth and Influence - Musk's recent merger of xAI and SpaceX resulted in a valuation of $1.25 trillion, making him the first individual to surpass $800 billion in wealth [3]. - Musk's portfolio includes significant stakes in Tesla and other ventures, positioning him as a key player in the future of technology and capital [3][5]. Group 2: Strategic Industries and Technologies - Musk's companies are not limited to automotive and aerospace; they encompass AI, space communication, and low-orbit internet, which are pivotal for global order [5][20]. - Tesla's Shanghai factory is projected to deliver 916,000 vehicles in 2024, accounting for half of global deliveries, while also collecting over 3 billion kilometers of autonomous driving data in China [7][9]. Group 3: National Security Implications - The Starlink project, initially aimed at providing internet access to remote areas, has deployed thousands of satellites that could potentially be used for military purposes, raising concerns about data sovereignty and security [9][11]. - Musk's xAI aims to integrate AI into various applications, creating a closed-loop ecosystem that could dominate standards and control key technologies, posing a challenge for Chinese companies [11][18]. Group 4: China's Response and Opportunities - The article suggests that Musk's presence in China has stimulated local innovation, exemplified by the rapid development of the electric vehicle supply chain [13][15]. - Despite challenges, Chinese companies are adapting and developing their own low-orbit satellite systems and AI capabilities, indicating a competitive response to Musk's influence [16][22]. Group 5: Future Competition Dynamics - The competition between Musk's enterprises and Chinese firms will not only be about market share but also about defining technological standards and controlling communication channels [20][22]. - The article emphasizes the need for China to recognize the new logic of cross-industry competition and to make breakthroughs in multiple fields to effectively respond to Musk's influence [22].

Core Viewpoint - The article emphasizes that while domestic computing infrastructure has improved, the real challenge for developers lies in the usability of these systems, particularly in the context of AI development, where the existing software ecosystem remains heavily reliant on established foreign tools and frameworks [1][2]. Group 1: Current State of AI Development - The AI landscape is vibrant with numerous models being released, yet the underlying software ecosystem's maturity is a significant bottleneck for deployment efficiency [11][12]. - The development of high-performance operators (算子) is crucial as they serve as the "translators" between AI algorithms and hardware, impacting inference speed, energy consumption, and compatibility [13][14]. Group 2: KernelCAT Introduction - KernelCAT is introduced as a local AI agent designed to accelerate computing and facilitate model migration, capable of handling both specialized tasks and general software engineering duties [17]. - Unlike traditional tools, KernelCAT combines intelligent code understanding and optimization with operational research algorithms to automate parameter tuning, significantly reducing the time and effort required for optimization [21][22]. Group 3: Performance and Competitive Edge - In tests, KernelCAT demonstrated superior performance compared to both open-source and commercial operators, achieving execution times as low as 0.0077 ms for 1M scale tasks, which translates to acceleration ratios exceeding 200% [26]. - KernelCAT's unique approach allows it to optimize operators effectively, showcasing its potential to compete with established solutions in the market [25][27]. Group 4: Ecosystem Challenges - The article highlights that over 90% of significant AI training tasks currently run on NVIDIA GPUs, with a developer ecosystem that includes over 5.9 million users and more than 400 operators, indicating a substantial barrier for domestic alternatives [28][30]. - The success of NVIDIA is attributed to its comprehensive control over software and algorithms, underscoring the importance of a mature ecosystem for hardware performance to be fully realized [32]. Group 5: Future Directions - KernelCAT represents a shift towards building self-evolving computational foundations, moving away from reliance on existing ecosystems to developing capabilities that can adapt and grow independently [39]. - The article concludes with an invitation for users to experience KernelCAT, indicating its ongoing development and potential for broader adoption in the industry [40].

Group 1: Financial Technology - In 2026, global liquidity is expected to remain reasonably ample, with the domestic monetary policy maintaining a moderately loose tone[14] - The digital RMB 2.0 will officially implement on January 1, 2026, transitioning from M0 to M1 currency attributes[18] - The CIPS network expansion will be a key focus starting February 1, 2026, as new rules for the RMB cross-border payment system come into effect[20] Group 2: AI Applications - The AI application landscape is shifting towards commercial monetization, with a focus on achieving breakeven after initial explosive growth[24] - C-end applications are dominated by major tech giants, making it difficult for smaller firms to survive in the market[40] - B-end applications are seeing some achieving unit economics (UE) breakeven, particularly in sectors with high product-market fit (PMF) like robotaxi[45] Group 3: AI Computing Power - Global demand for AI computing power is on the rise, with domestic internet companies being the largest consumers of intelligent computing servers[3] - Domestic chip manufacturers are making significant breakthroughs, with companies like Huawei and Cambricon showing strong growth potential[3] - The shift towards scale-up supernode architectures is expected to accelerate, enhancing overall system performance[3] Group 4: AI Energy - The AIDC power supply paradigm is evolving towards 800V HVDC systems, driven by the need for higher power density and efficiency[4] - Nuclear fusion is being explored as a long-term energy solution, with significant advancements expected within the next five years[7]

Core Viewpoint - The article discusses the ongoing competition between the US and China in the field of artificial intelligence (AI), highlighting the advancements made by both countries and the differing approaches they take towards AI development [2][3][4]. Group 1: Historical Context and Current Landscape - The origins of AI can be traced back to the 1956 Dartmouth Conference, with the US leading the evolution of algorithms and frameworks for a significant period [2]. - Major milestones in AI include AlphaGo's victory in 2016 and the rapid user adoption of ChatGPT in 2022, showcasing the US's early advantages in algorithmic development [2]. - The current AI boom in the US is characterized by a focus on scaling models and computational resources, which has led to significant investments in AI chips and data centers [4]. Group 2: Challenges and Opportunities - The scaling law, while a foundational principle for large models, faces diminishing returns, raising questions about whether increasing computational power is the only path to AI advancement [4]. - China has made substantial progress in AI through practical applications, demonstrating that it does not lag behind the US in terms of generational capabilities [4][6]. - The US's attempts to restrict China's access to chip technology have inadvertently spurred the development of a domestic supply chain in China, showcasing the effectiveness of its coordinated national strategy [6][7]. Group 3: Resource and Talent Advantages - China boasts a significant advantage in electricity supply, with a total installed capacity of 3.8 billion kilowatts and an expected annual electricity consumption of approximately 10.4 trillion kilowatt-hours by 2025, which is more than double that of the US [7]. - The talent pool in China is vast, with over 5 million graduates in STEM fields annually, providing a strong foundation for algorithm research and AI development [7]. Group 4: Future Directions and Philosophical Perspectives - The article emphasizes the importance of practical applications of AI, suggesting that true advancements will come from real-world interactions rather than theoretical models [9]. - The concept of embodied intelligence is highlighted as a potential area of divergence between the US and China, with China leveraging its market to explore both high-end robotics and practical applications in various sectors [9][10]. - The article critiques the US's zero-sum approach to AI, contrasting it with China's philosophy of shared development and collaboration with other nations to bridge the global digital divide [12][14].

Group 1 - The Guangdong Provincial Government is focusing on enhancing human investment and social welfare to support high-quality development during the 14th Five-Year Plan period [7][8][14] - Key initiatives include implementing employment strategies, expanding educational resources, and improving healthcare services to address aging population challenges [10][11][12][14] - The government aims to strengthen the social security network and increase coverage for flexible employment and migrant workers [13][14] Group 2 - The Guangdong Provincial Government plans to build a modern industrial system centered on advanced manufacturing, optimizing traditional industries while fostering emerging sectors like new energy and biotechnology [16][17][18] - By 2025, the province's industrial revenue is expected to exceed 19 trillion yuan, with advanced manufacturing and high-tech manufacturing accounting for over 50% and 30% of industrial output, respectively [23][24] - The government is committed to enhancing the safety of industrial supply chains and promoting digital transformation among enterprises [26][27] Group 3 - The Guangdong Provincial Government is prioritizing agricultural modernization and the development of agricultural industry clusters, aiming to strengthen the province's agricultural capabilities [60][67] - Significant achievements include the collection of 368,000 agricultural genetic resources and the development of 30 new rice varieties, representing 23.4% of the national total [62][63] - The government plans to establish 10 trillion-yuan-level and 20 hundred-billion-yuan-level agricultural industry clusters by 2027 [68] Group 4 - The Guangdong Provincial Government is enhancing foreign trade quality and stability, with a target of 9.49 trillion yuan in foreign trade by 2025, reflecting a 4.4% growth [83][84] - The strategy includes diversifying markets and supporting enterprises in expanding their international presence, particularly in emerging markets [89][90] - The government aims to cultivate export industry clusters in electronics, light industry, and artificial intelligence, among others [91][92]

Group 1 - Musk predicts that the existing social model has about 2000 days left, with AI expected to fundamentally change everything by 2031 [1] - AGI (Artificial General Intelligence) may be realized by 2026, and by 2030, AI's total intelligence could surpass that of all humans combined [1] - The rapid advancement of AI is likened to a snowball effect, with significant implications for various job sectors, particularly for white-collar workers [3] Group 2 - The transition from 3nm to 2nm chips shows diminishing returns, indicating that the limits of Moore's Law are approaching [3] - High-profile job sectors such as law and accounting are at risk, with a Goldman Sachs report stating that 300 million jobs globally could be at risk of replacement [3] - AI's efficiency in tasks like contract review and coding is leading to a shift in job roles, with many workers becoming mere facilitators [3] Group 3 - Musk emphasizes that electricity supply is a critical bottleneck for AI development, with predictions that global AI data centers will consume more electricity than Japan by 2026 [5] - China is projected to have three times the electricity output of the U.S. by 2026, with a significant capacity for data center demands [5] - China's solar power capacity is substantial, with 1500 GW of production annually, contributing to its competitive edge in AI computing [5] Group 4 - China's computing power is ranked second globally, with a market size projected to reach 835.1 billion yuan by 2025, growing over 30% annually [7] - The country is establishing eight major computing hubs and has the highest number of supercomputers globally, accounting for 45% of the total [7] - Policies are being implemented to regulate AI-generated content and ensure data security, fostering a controlled yet vibrant AI development environment [7] Group 5 - Musk expresses optimism about the technological benefits of AI, emphasizing the need for collaboration to avoid resource wastage [9] - China is expected to lead in computing capabilities, with projections of reaching over 450 EFLOPS by 2030 [9] - The shift towards AI in various sectors, including e-commerce and healthcare, is anticipated to create new opportunities, despite the challenges of transitioning from traditional models [9]