21世纪经济报道记者 易妍君 临近年末，A股波动加大，但机构调研热度未减。 据Wind统计，截至12月21日，本月内至少已有472家A股上市公司接受了机构调研。其中，机构关注度排名前十（以调研机构家数为准）的上 市公司分布在计算机设备和附件、集成电路、汽车制造、石油天然气设备与服务、工业机械、电气部件与设备、医药等行业，这些公司大多为 Wind新质生产力概念股。 受访人士向21世纪经济报道记者指出，机构调研逻辑正在转向"业绩兑现确定性与技术迭代潜力"双轮驱动，更加注重企业长期价值与产业趋势 的契合度。 扎堆调研新质生产力 近期，各类资产管理机构的调研持续围绕科技主线展开。部分"含科量"较高的上市公司，往往会吸引券商、公募基金、私募基金、保险公司及 保险资管等机构扎堆调研。 Wind数据显示，12月1日—12月21日，中科曙光、海光信息、长安汽车、杰瑞股份、博盈特焊至少获得了365家、365家、227家、221家、139 家机构调研，为机构调研热度排名前五的上市公司。 同时，调研一品红、伟创电气、广联航空、华通线缆的机构数量均超过100家，分别为：119家、112家、102家、101家；调研热度排在第十位 的佐 ...

Core Insights - The VLA (Visual-Language-Action) model faces challenges in training due to the scarcity and complexity of physical world data, which is essential for enhancing its capabilities [2] - The shift from a machine-centered to a human-centered AI research paradigm is necessary for training embodied intelligence models [2] Group 1: ACE Paradigm - The ACE (Action-Centric Embodiment) paradigm focuses on human interaction with the physical world as the starting point for research, utilizing environmental data collection as a core engine [3] - The ACE framework integrates first-person and third-person video, haptic information, motion trajectories, and voice data to create a physics-based 3D asset library [3] Group 2: Open Source Model - The "Awakening World Model 3.0" has been released as an open-source and commercially applicable model, aiming to unify understanding across different domains by integrating physical laws, human behavior, and real machine actions [5] - The platform supports 11 major categories and 54 subcategories, covering 115 types of embodied scenarios, allowing developers to quickly generate visual task simulations with simple commands [5] Group 3: Industry Collaboration - The company collaborates with various robotics firms to integrate the ACE paradigm and world model with hardware solutions tailored for different scenarios [6] - Partnerships with domestic chip manufacturers enhance the computational capabilities of the Awakening World Model 3.0 [6] Group 4: Market Applications - In the short term, the focus will be on deploying quadruped robots with autonomous navigation capabilities in security and inspection sectors [6] - The medium-term strategy includes addressing labor-intensive logistics scenarios, while long-term goals involve exploring applications in home environments, contingent on resolving safety and liability issues [6] Group 5: Industry Trends - The ACE paradigm aligns with trends observed in companies like Tesla and Figure AI, indicating a significant opportunity in the sector over the next one to two years [7]

Core Insights - The computing power industry is undergoing a significant shift from a focus on single-point performance to system efficiency and multi-party collaboration in response to the demands of large models [1][2][3] Group 1: Industry Trends - The consensus among industry leaders is that the competition in computing power has evolved, necessitating a shift from a full-stack approach to a collaborative system engineering model [1][2] - As the scale of models increases to trillions of parameters, the challenges faced by computing systems extend beyond peak computing power to include interconnect bandwidth, storage hierarchy, power cooling, and system stability [2][3] - Traditional computing nodes are becoming inadequate for supporting large-scale models, leading to a consensus shift towards super-node and super-cluster models that utilize high-speed buses to connect multiple GPUs [3] Group 2: Challenges in the Ecosystem - The full-stack self-research model adopted by many domestic manufacturers has led to increased internal competition and fragmentation, creating multiple closed ecosystems that complicate user experiences [4][5] - Users face significant challenges in adapting to various chip architectures, leading to high costs and reduced development efficiency due to the need for extensive optimization and adaptation [5][6] - The lack of a cohesive ecosystem in domestic AI development is seen as a bottleneck, with manufacturers struggling to achieve seamless integration between hardware and software [6] Group 3: Shift to Open Computing - Open computing is being emphasized as a necessary approach, requiring manufacturers to move away from a "one company does it all" mentality towards a collaborative model where multiple firms contribute to different layers of the system [7][8] - The transition to open computing involves significant challenges, including the need to relinquish some control and profit margins, as well as establishing effective coordination mechanisms among various stakeholders [7][8] - A layered decoupling of the industry chain is essential for open computing, where different companies work on components like chips, interconnects, and storage while maintaining unified standards to ensure system efficiency [8] Group 4: Future Outlook - The coexistence of tightly coupled closed systems and open collaborative systems is expected to persist in the rich application landscape of the domestic market [9] - The ability to create an efficient, collaborative, and sustainably evolving system will be a critical factor determining the survival of manufacturers in the evolving landscape of large models and super clusters [9]

Core Viewpoint - The competitive rules of China's AI industry are being rewritten, shifting the focus from hardware performance to ecological collaboration efficiency as a new measure of competitiveness in the AI computing industry [1][4]. Group 1: Industry Trends - The HAIC2025 event showcased over 2,500 upstream and downstream enterprises, indicating a trend towards breaking down "technology walls" and "ecological walls" to achieve a "group leap" in the AI computing industry [1][3]. - The concept of "open architecture" is becoming essential for overcoming industry bottlenecks, as it promotes shared key technologies and lowers the barriers for research and application [4][6]. Group 2: Open Architecture and Collaboration - The AI computing open architecture aims to transform the industry from "physical stacking" to "chemical fusion," addressing issues such as high-end computing power shortages and high innovation thresholds [6][10]. - The launch of the scaleX super cluster, capable of deploying 10,240 AI accelerator cards and exceeding 5 EFlops in total computing power, demonstrates the technical feasibility and advantages of the open architecture [4][6]. Group 3: Partner Practices and Innovations - Companies like Qingdao Thunder Technology and Unisplendour have successfully utilized the open architecture to lower R&D costs and enhance product compatibility, leading to innovations in various industry scenarios [7][8]. - The collaborative model of "multi-vendor cooperation and shared foundation support" has proven effective in driving the domestic AI ecosystem into a "group leap" phase, with significant advancements in sectors like gaming and healthcare [7][9]. Group 4: Future Outlook - The establishment of the "AI Computing Open Architecture Joint Laboratory" aims to invest 1 billion yuan over three years, involving over 150 member units and 1,000 R&D personnel to enhance domestic AI capabilities [12]. - The ongoing reinforcement of the open architecture's "linking" role is expected to lead to a higher quality "group leap" in the domestic AI ecosystem, providing solid support for the implementation of the "Artificial Intelligence +" strategy [12].

Group 1 - In December, nearly 500 companies have been surveyed by institutional investors, with a strong focus on the technology sector [1][12] - A total of 471 companies in the A-share market have been publicly surveyed by institutional investors since December, with 23 companies receiving over 50 institutional visits and 9 companies over 100 [2][13] - Among the most frequently surveyed companies, Zhongke Shuguang and Haiguang Information attracted the highest attention, with 365 institutions participating in their surveys [3][14] Group 2 - Zhongke Shuguang launched the scaleX Wanka Super Group at the 2025 Photonic Organization AI Innovation Technology Conference, focusing on trillion-parameter large models and scientific intelligence scenarios [4][15] - Jie Rui shares have made significant breakthroughs in the North American market, signing a sales contract for generator sets worth over 100 million USD, marking a key business breakthrough in the high-end power market [4][15] - Companies like Boying Welding and Ice Wheel Environment have organized over 10 survey activities each this month, indicating high interest in gas turbine concepts [5][16] Group 3 - Several companies that received institutional attention have seen significant stock price increases, with Hualing Cable experiencing an 83.61% increase in December [6][17] - Shaanxi Huada's stock surge is linked to its plan to acquire 100% of Huajing Microelectronics, entering the lucrative optical module market [8][18] - High-profile institutions, such as Gao Yi Asset, have conducted surveys on 11 companies this month, including Boying Welding and Jie Rui shares [9][19] Group 4 - The survey of Jie Rui shares revealed the company's commitment to continue deepening its presence in data centers, industrial energy, and new power systems [10][20] - The company has expanded its production capacity in the U.S. to meet the demand for gas turbine generator equipment in North America [10][20] - A focus on humanoid robots and AI vision technology was highlighted during the survey of Aobi Zhongguang, showcasing its competitive edge in the robotics sector [11][21]

*免责声明：文章内容仅供参考，不构成投资建议 | | 经纬恒润 | 12 | | --- | --- | --- | | | 长安汽车 | 12 | | | 品红 | 12 | | | 走瘦线缆 | 12 | | | 中粮科技 | 12 | | | 中科曙光 | 1こ | | | 海米信息 | 12 | | 嘉实基金 | | | | 中瓷电子 | 12 | | --- | --- | | 永鼎股份 | 12 | | 本钢板材 | 12 | | 中信出版 | 12 | | 好莱客 | 12 | | 英威腾 | 12 | 知名机构近一周 上周共计21家公司获知名机构调研 随其后；个股上，长安汽车获最多 式号牌在长安汽车启用，其后分别 | 机构名称 | 股票名称 | 道 | | --- | --- | --- | | | 长安汽车 | 12 | | | 品红 | 12 | | | == | 1 | | 高毅资产 | 京嘉償 | _ ﮮ | | --- | --- | --- | | | 冰轮环境 | 12 | | | 杰瑞股份 | 12 | | | 睿创微纳 | 12 | | | 中信出版 | | | | 潍柴动力 ...

Market Performance - On December 22, A-shares saw a collective increase in the three major indices, with the Shanghai Composite Index rising by 0.69% to 3917.36 points, the Shenzhen Component Index increasing by 1.47% to 13332.73 points, and the ChiNext Index climbing by 2.23% to 3191.98 points [1] Fund Manager Changes - From December 20 to December 22, a total of 58 fund managers experienced changes in their positions, with 652 fund products having manager changes in the past 30 days [3] - The reasons for the changes included 23 fund managers leaving due to job changes, 5 due to product expiration, and 1 for personal reasons [3] - During the same period, 88 fund products announced new fund manager appointments involving 30 fund managers [5] Fund Manager Performance - Zhang Xiaonan, a fund manager at Invesco Great Wall, currently manages assets totaling 30.607 billion yuan, with the highest return product being the Invesco Great Wall Nasdaq Technology ETF, which achieved a return of 134.72% over 2 years and 316 days [4] - Zhang Dazheng, a fund manager at Yingda Fund, manages assets of 12.372 billion yuan, with the highest return product being Yingda Strategy Preferred A, which gained 77.05% over 5 years and 352 days [6] Fund Research Activity - In the past month (November 22 to December 22), Bosera Fund conducted the most company research, engaging with 39 listed companies, followed by Southern Fund, Huaxia Fund, and Huitianfu Fund, which researched 36, 32, and 31 companies respectively [8] - The most researched industry was specialized equipment, with 167 instances, followed by the semiconductor industry with 121 instances [8] Individual Stock Research - The most focused stock by public funds in the last month was Zhongke Shuguang, with 117 fund management companies participating in its research, followed by Haiguang Information and Changan Automobile, each with 117 and 82 participating fund managers respectively [9] - In the last week (December 15 to December 22), Changan Automobile was the most researched company, with 68 fund institutions involved [9]

Group 1 - Nvidia's cabinet liquid cooling market is expected to accelerate, with an estimated market size of $6.9 billion to $9.7 billion by 2026, driven by orders for approximately 14 million GPUs from Blackwell and Rubin [1] - The power of Nvidia's GPU chips is projected to increase significantly, from approximately 1000W for B200 to 2300W for R200 by 2026, and potentially over 4000W for R300 by 2027 [1] - Google's TPUv7 and above are expected to ship around 2.2 to 2.3 million units in 2026, leading to a projected market size of $2.4 billion to $2.9 billion for Google's cabinet liquid cooling systems [2] Group 2 - The domestic liquid cooling server market in China is forecasted to reach $10.2 billion by 2028, with a compound annual growth rate of 47.6% from 2023 to 2028 [3] - The current penetration rate of liquid cooling in servers is only 5%, indicating significant growth potential as the market expands [3] - Huawei's CloudMatrix384 super node has already sold over 300 units, and the introduction of new super nodes is expected to further drive demand for liquid cooling solutions in the domestic market [4] Group 3 - 2026 is anticipated to be a pivotal year for the industrialization of liquid cooling, with recommendations to focus on leading companies with technological barriers and those that can enter the supply chains of major domestic and international firms [5] - Companies such as Yingweike, Sixuan New Materials, Yidong Electronics, Hongfuhan, Shuo Beid, Jie Bang Technology, Xiangxin Technology, and Shenling Environment are highlighted as potential investment targets [5]

Group 1 - The technology sector is experiencing a collective surge, particularly in chips, communications, computer equipment, and consumer electronics, with significant gains observed in various ETFs [1] - The digital economy ETF, 富国 (159385), has seen an intraday increase of 3.11%, while the 科创芯片 ETF (588810) and chip leader ETF (516640) have risen by 3.06% and 3.05% respectively [1] - Notable stocks within the digital economy ETF include 瓷电子, which has surged over 7%, and 中芯国际, which has increased by over 6% [1] Group 2 - The Ministry of Commerce and five other departments have issued an action plan to promote high-quality development in service outsourcing, encouraging innovation and the development of cloud computing and supercomputing services in resource-rich cities [1] - Local initiatives include Anhui's "14th Five-Year Plan" to advance digital construction and create a national integrated data market hub, as well as Shanghai's announcement of 41 local standards related to the digital economy [1] - The robotics industry is highlighted by Wang Lihong's concert in Chengdu, showcasing the world's first robot dance stage, which demonstrates breakthroughs in humanoid robot technology and has received recognition from Tesla's CEO Elon Musk [1] Group 3 - The digital economy ETF 富国 (159385) closely tracks the 中证诚通国企数字经济指数 (931529.CSI), which includes leading companies in integrated circuit manufacturing, semiconductor equipment, digital chip design, telecom operators, and communication devices [2] - The top ten constituents of this index include 中芯国际, 北方华创, 海光信息, 中科曙光, 中微公司, and 中兴通讯 [2]

人工智能AIETF（515070）跟踪CS人工智能主题指数（930713），成分股选取为人工智能提供技术、 基础资源以及应用端个股，聚集人工智能产业链上中游，俗称"机器人"大脑"缔造者"，万物互联"地 基"。前十大权重股包括中际旭创、新易盛、寒武纪-U、中科曙光、科大讯飞、豪威集团、海康威视、 澜起科技、金山办公、紫光股份等国内科技龙头。 A股科技赛道午后延续强势，CPO、无人驾驶、人工智能、人形机器人、存储板块全线上涨，沪市规模 最大的人工智能AIETF（515070）盘中涨2.08%，其持仓股新易盛、中际旭创涨幅均超6%，北京君正、 浪潮信息、芯原股份等股涨幅居前。 消息方面，据南方财经报道，深圳功能型无人车投放总量已达 1218 台（其中包含无人物流车 825 台），车辆数在全国一线城市中位列第一，累计开放运行线路 1594 条、总里程达 5534 公里。今年以 来，深圳等地颁发 L4 级自动驾驶微型货车测试牌照，标志着自动驾驶货运服务进入多场景、规模化发 展阶段。报道还提到，我国拥有全球最大的自动配送市场。截至 2025 年上半年，全国已有 103 个城市 开放无人配送车辆路权，全国无人配送车保有量突 ...