文 | 脑极体 每到岁末年初，我们就会被众多研究机构的预测所包围。不少科技公司的朋友，也希望跟我们交流一下 对来年的行业趋势的看法。 他们都表示，平时忙于本职工作，往往只关注自己所在的特定领域，以及自家和友商明年想推什么产 品。到了年底复盘、年度规划的时候，更渴望跳出单一视角的局限，以更全面、宏观的维度，审视整个 行业的变化。找来找去，似乎就我们平时关注的技术领域格外全面，AI、云、终端、通信、计算、软 件等都有涉及。 为啥不只盯着AI算法，非要关注这么多技术领域？背后的逻辑有点类似查理·芒格的格栅理论，这么多 技术概念相互交织，才能构建多因素综合的认知框架，对产业进行全局观察和综合研判，从而预测某一 个具体技术可不可靠、能否落地。 结合2025年我们对多个技术领域的实地走访与观察，一个核心感受是：2026年，科技行业不会再上演概 念的狂飙突进，开始进入现有技术能力的消化期。 诸多热点退潮的2026，将是一个祛魅之年。 当浮华褪去，比起踩中风口，提高容错率才是对个人和企业真正重要的事情。所以我们不打算预测来年 热点，更希望帮大家预测下什么会凉，提前祛魅。 提到祛魅之年，首当其冲的就是英伟达叙事。 智算市场的2 ...

Core Viewpoint - The article emphasizes that 2026 is expected to be a year of significant harvest for domestic hard technology in the electronics industry, driven by advancements in AI and a consensus on performance trends within the AI industry chain [3][7]. Group 1: AI Industry Trends - The AI industry is transitioning from divergence to consensus in performance trends, with a notable recovery since the second half of 2023, marked by the return of Huawei's Mate series [3][7]. - The electronics sector has experienced a significant valuation expansion, aided by the rapid growth of passive funds and the resonance of macro policy, inventory cycles, and AI innovation cycles [3][7]. - As of December 16, 2025, the electronics sector has risen by 40.22%, ranking third among all industries [7][16]. Group 2: AI Model Evolution - The evolution of AI models is characterized by innovations in architecture, such as the mixture of experts (MoE) framework, which enhances efficiency by reducing computational load [27]. - The emergence of large models, like OpenAI's GPT-4, showcases the correlation between model size and performance, leading to significant advancements in understanding and reasoning capabilities [27]. - The demand for improved model efficiency has led to innovations in attention mechanisms, which lower computational complexity and memory requirements [27][28]. Group 3: Computing Power and Storage - The domestic chip industry is actively updating and iterating, with companies like Huawei planning to launch new chips in 2026, while the storage sector is expected to face shortages and price increases throughout the year [9]. - The demand for AI-driven storage solutions is projected to increase, with DRAM bit demand expected to rise by 26% year-on-year in 2026, driven by AI applications [9]. Group 4: Power and Connectivity - The optimization of data transfer and communication within servers is becoming a critical breakthrough for enhancing computing power, with the global high-speed interconnect chip market expected to reach $21.2 billion by 2030 [11]. - The increasing power consumption of data center chips necessitates advancements in power supply architectures, with a shift towards high-density power solutions [11]. Group 5: Semiconductor Industry - The semiconductor sector is anticipated to benefit from a recovery in demand, with a focus on domestic manufacturing and the rise of analog chips, which are expected to see increased adoption due to their potential for localization [12]. - The global semiconductor market is projected to achieve double-digit growth for three consecutive years from 2024 to 2026, driven by advancements in AI and domestic chip design [12][14].

当地时间12月8日，美国总统特朗普在社媒平台上称，在确保美国国家安全的前提下，将"允许英伟达向 中国及其他国家的合格客户交付其H200芯片产品"，但会对每颗芯片收取一定费用。 特朗普还表示，美国商务部正在敲定具体细节，同样的方案也将适用于超微半导体、英特尔以及其他美 国公司，美方将从相关芯片出口中收取25%的分成。在特朗普宣布这一消息后，英伟达股价在盘后交易 中上涨了1.2%。 对此，英伟达方面向《中国经营报》记者确认了该消息，并表示："向商业客户供应H200是一种值得肯 定的举措。" 据了解，英伟达H200芯片发布于2023年11月，2024年第二季度开始供货，核心升级在于全球首创的 141GB HBM3e内存系统，使处理超大模型的能力实现质的飞跃。 相比H100，英伟达H200的内存容量提升76%，带宽增加43%，AI推理性能提升最高90%，特别适合大语 言模型和科学计算。由于市场波动和销售渠道不同，英伟达H200的当前市场报价主要集中在20万至25 万元区间（约合2.8万至3.5万美元），而包含多块H200 GPU、服务器、网络和冷却基础设施在内的整体 H200整机系统（如DGX H200）售价可能超过 ...

2018年龙岗首次登顶全国工业百强区，此后连续7年蝉联该称号。这一阶段园区发展进入集群化、协同 化的新阶段。2017年，龙岗创新性提出建设数字创意产业走廊，规划"一廊三核多支点"布局，将天安云 谷、大运软件小镇等纳入其中，串联起35个文化产业园区，形成数字硬件、数字内容等多元业态的产业 带。面对高科技领域"卡脖子"难题，龙岗以园区为载体主动破局，建设罗山科技园，推进工业软件攻 关。2020年，与华为联手打造全国最大规模的"华为（龙岗）工业互联网创新中心"，推动数字技术与制 造业深度融合；2021年建成全省首个工业软件及工业云攻关基地，让园区成为核心技术突破的重要阵 地。此外，龙岗还开始推动传统产业园区转型，为眼镜等传统产业的园区量身定制升级路径。 深圳龙岗产业园区的发展，是一部从承接低端加工贸易起步，到培育出世界级产业龙头，再到打造多元 高端产业集群的转型史诗，不同阶段的产业园区作为核心载体，见证并推动了龙岗从农田荒山蜕变为全 国工业百强区榜首的跨越： 1. 起步阶段（1993 - 2000年）：搭建工业框架，承接龙头落地 1993年龙岗建区之初，经济以"三来一补"的外向型加工贸易为主，为摆脱落后局面，龙岗规 ...

Group 1: AI Computing Power - The global infrastructure wave is driving significant growth in AI computing power, with major cloud service providers (CSPs) expected to increase capital expenditures (CapEx) to over $600 billion in 2026, representing a 40% year-on-year increase [5][24][25] - NVIDIA anticipates that the total shipment of Blackwell and Rubin GPUs will reach 20 million units by the end of 2026, generating approximately $500 billion in sales [31][33] - The demand for AI servers is expected to maintain high growth, with shipments projected to rise from 1.6 million units in 2024 to 2.4 million units in 2026 [25][28] Group 2: AI Storage - The storage industry is entering a "super cycle" due to a rebound in demand driven by AI applications, with DRAM and NAND Flash prices expected to rise significantly [52][64] - Major storage manufacturers have successfully reversed the supply-demand imbalance through strict production control, leading to a clear upward trend in prices for both DRAM and NAND Flash [52][64] - The demand for high-capacity SSDs is rapidly increasing, particularly in AI training, which is accelerating the replacement of traditional HDDs with QLC SSDs [7][52] Group 3: End-Side AI - AI is reshaping the hardware landscape for smart terminals, with AI smartphone penetration expected to rise from approximately 18% in 2024 to 45% in 2026 [7][19] - The success of AI glasses, such as Ray-Ban Meta, indicates a growing market for AI-integrated wearable technology, with significant sales growth anticipated in 2026 [7][20] - The development of humanoid robots is gaining momentum, with traditional consumer electronics manufacturers entering the robotics supply chain, driven by advancements in AI models [7][21] Group 4: Investment Recommendations - Recommended companies in the AI computing power sector include Industrial Fulian, Huadian Technology, and Shenghong Technology for overseas chains, and Cambrian, Chipone, and SMIC for domestic chains [7][8] - In the AI storage sector, companies like Demingli, Jiangbolong, and Baiwei Storage are highlighted, along with niche players such as Zhaoyi Innovation and Beijing Junzheng [7][8] - For end-side AI, recommended companies include Rockchip, Lexin Technology, and Lens Technology, focusing on SoC and consumer electronics [7][8]

Core Insights - The article emphasizes the importance of Guangdong's development under the guidance of Xi Jinping's leadership, focusing on high-quality growth and modernization efforts [1][2][15] - Guangdong is positioned as a leader in reform and innovation, with significant advancements in technology and governance aimed at enhancing efficiency and global connectivity [2][11][15] Innovation and Technology - Guangdong is transitioning from "following" to "leading" in innovation, with advancements in autonomous driving and other technologies becoming commonplace [3][5] - The region has established a robust innovation ecosystem, with significant investments in research and development, exemplified by companies like BYD and Huawei [5][6] - Guangdong's innovation capabilities have been recognized nationally, maintaining the top position in regional innovation for eight consecutive years [6][10] Reform and Governance - The province is undergoing systemic reforms to improve administrative efficiency, making processes more user-friendly for residents and businesses [9][10] - Guangdong's reforms include enhancing the investment environment and streamlining bureaucratic procedures, which have led to a significant increase in foreign investment [11][14] Open Economy and Global Integration - Guangdong is enhancing its role as a global hub through infrastructure improvements and regulatory reforms, facilitating smoother cross-border interactions [11][13] - The region has seen a substantial increase in foreign investment, with 24,000 new foreign enterprises established in the first nine months of the year, marking a 33.7% increase [14][15] - The establishment of the Guangdong-Hong Kong-Macao Greater Bay Area is pivotal in driving regional integration and attracting global investments [15][16]

Core Viewpoint - The article discusses the escalating tensions between the US and China, highlighting the recent retaliatory measures taken by China in response to US tariffs and sanctions, and emphasizes the shift in power dynamics, suggesting a "strong China, weak America" narrative. Group 1: US-China Trade Relations - The US has repeatedly initiated hostile actions against China, which China has responded to with significant countermeasures, indicating a pattern of reciprocal actions [1][2][11] - The US's attempt to impose discriminatory fees on Chinese vessels is viewed as an unreasonable tactic, reflecting a misunderstanding of its own position in the global maritime industry [3][4][8] Group 2: Maritime Industry Dynamics - In 2023, China constructed a total of 32.86 million tons of commercial ships, holding a 51% share of the global market, while the US only built 64,800 tons, representing a mere 0.1% market share [7] - Despite the US's attempts to influence global shipping and shipbuilding dynamics, the actual impact of its policies is limited, as evidenced by the recovery of Chinese shipyards' order volumes [9][12] Group 3: Semiconductor Industry and Sanctions - The US has intensified its sanctions against Chinese semiconductor companies, with a record number of firms added to the entity list, indicating a strategic focus on this sector [13][14] - The US's export controls have expanded significantly, affecting a wide range of Chinese companies and complicating international supply chains [15][18] Group 4: Perception of Power Dynamics - The article posits that the overall power dynamic has shifted, with China now perceived as stronger relative to the US, particularly in manufacturing and technology sectors [23][24][26] - The narrative of "strong China, weak America" is gaining traction, as evidenced by China's advancements in various industries, including manufacturing and military technology [25][42] Group 5: Global Reactions and Future Implications - The article notes a growing recognition among global leaders and businesses of China's rising strength and the need to adapt to this new reality [41][42] - The ongoing trade tensions and retaliatory measures are expected to continue shaping the landscape of US-China relations, with potential long-term implications for global trade and industry dynamics [22][42]

Core Insights - The report highlights the exponential growth in AI model parameters from hundreds of millions to trillions, with global AI computing demand doubling every 3-4 months, significantly outpacing traditional Moore's Law [14][15][17] - The training cost for models like Llama 4 is projected to exceed $300 million by 2025, a 66-fold increase compared to the $4.5 million cost for training GPT-3 in 2020, indicating a critical need for heterogeneous computing solutions [15][17] - Heterogeneous computing, integrating various processing units like CPU, GPU, FPGA, and ASIC, is essential to meet diverse computational demands across different AI applications [18][29] Group 1: Industry Trends - The global AI computing market is expected to grow significantly, with China's intelligent computing scale projected to reach 1,037.3 EFLOPS by 2025, and the AI server market anticipated to hit $300 billion by the same year [26][28] - The "East Data West Calculation" initiative in China aims to enhance computing infrastructure, with over 250 optical cables planned to improve connectivity and efficiency [24][25] - The report emphasizes the increasing participation of domestic tech giants like Alibaba, Tencent, and Baidu in AI chip and computing infrastructure investments, fostering a robust ecosystem for AI development [26][28] Group 2: Technological Developments - The report discusses the evolution of AI models, with significant advancements in architectures such as the Mixture of Experts (MoE) model, which allows for efficient scaling while reducing computational costs [39][40] - Open-source models are gaining traction, with various series like GLM, Llama, and Qwen contributing to the democratization of AI technology and fostering innovation [41][42] - The integration of heterogeneous computing is seen as a pathway to optimize performance and efficiency, addressing the challenges posed by diverse computational requirements in AI applications [19][29]

Core Insights - Chinese technology companies are demonstrating that they can thrive without relying on Nvidia chips, as they form partnerships with Huawei to develop their own AI capabilities [1][2] - The Yangtze River Delta, where Hefei is located, contributes significantly to China's economy, accounting for 45% of the national output [1] Company Developments - iFlytek has begun using Huawei's Ascend chips, marking a shift away from reliance on American technology and providing Huawei with a reliable customer [2] - iFlytek's AI translation software team acknowledges that while U.S. sanctions pose challenges, collaboration with Huawei has helped mitigate these obstacles [2] Industry Trends - The U.S. efforts to curb the growth of Chinese tech firms are prompting these companies to seek independence from American chip suppliers [2] - Huawei is working on strategies to enhance its AI chip capabilities, aiming to reduce Nvidia's dominance in the AI sector [2] - Chinese companies are making progress in developing domestic alternatives to foreign technology, indicating a move towards self-sufficiency in AI [2]

Core Viewpoint - The domestic AI chip market in China is undergoing a significant transformation, with a focus on "de-NVIDIA" efforts led by major tech companies like Alibaba and Baidu, aiming to challenge NVIDIA's dominance in the AI chip sector [1][3]. Group 1: Market Dynamics - Chinese tech giants are actively promoting the development of self-researched AI chips, with Alibaba and Baidu announcing that their core AI models will partially utilize self-developed chips [1][3]. - Since late August, the stock prices of Baidu and Alibaba have surged by approximately 50% [1]. - The geopolitical tensions and concerns over the stability and security of the AI supply chain are driving the "de-NVIDIA" movement in China [3][5]. Group 2: NVIDIA's Challenges - NVIDIA faced a significant negative impact due to export restrictions on its H20 chip, leading to a stock impairment of about $4.5 billion in Q1 [5]. - Revenue from mainland China for NVIDIA dropped to $2.77 billion in Q2 of FY2026, a nearly 50% decline, reducing its market share from 85% to 70% in China [5][11]. Group 3: Rise of Domestic Chips - Domestic custom AI chips are rapidly emerging, with products like Alibaba's PPU chip and Huawei's Ascend series showing performance that rivals or exceeds NVIDIA's offerings [7][9]. - The PPU chip's single-card cost is approximately 40% lower than the imported H20 chip, highlighting the cost advantage of domestic solutions [7]. - IDC forecasts that by 2024, domestic AI chip brands will significantly increase their market share to 30% [11][13]. Group 4: Industry Evolution - The shift towards customized AI chips mirrors the evolution of smartphone chips from generic to specialized designs, driven by the need for better performance and cost efficiency [16][19]. - The transition from general-purpose GPUs to customized chips is essential for meeting the specific demands of AI inference tasks, which require lower power consumption and reduced latency [20][21]. - The development of domestic chip design and supply chains is enabling Chinese companies to enhance their competitiveness in the global market [23][24].