1月7日，当虹科技跌5.07%，截至发稿，报52.20元/股，成交4.48亿元，换手率7.60%，总市值57.73亿 元。 截至发稿，张鹏累计任职时间10年135天，现任基金资产总规模9.66亿元，任职期间最佳基金回报 72.42%， 任职期间最差基金回报22%。 资料显示，杭州当虹科技股份有限公司位于浙江省杭州市滨江区众创路309号，成立日期2010年5月12 日，上市日期2019年12月11日，公司主营业务涉及专注于智能视频技术的算法研究,视频编转码、智能 人像识别、全平台播放、视频云服务等核心算法,提供智能视频解决方案和视频云服务。主营业务收入 构成为：传媒文化产品及解决方案73.26%，车载智能座舱产品17.20%，工业与卫星产品及解决方案 7.27%，租赁收入2.07%，其他0.21%。 风险提示：市场有风险，投资需谨慎。本文为AI大模型自动发布，任何在本文出现的信息（包括但不 限于个股、评论、预测、图表、指标、理论、任何形式的表述等）均只作为参考，不构成个人投资建 议。 责任编辑：小浪快报 从基金十大重仓股角度 数据显示，融通基金旗下1只基金重仓当虹科技。融通互联网传媒灵活配置混合（001150） ...

Core Viewpoint - Donghong Technology experienced a decline of 5.05% on October 14, with a stock price of 52.03 CNY per share and a total market capitalization of 5.755 billion CNY [1] Company Overview - Donghong Technology Co., Ltd. was established on May 12, 2010, and went public on December 11, 2019. The company specializes in intelligent video technology, focusing on algorithm research, video encoding and decoding, intelligent portrait recognition, cross-platform playback, and video cloud services [1] - The revenue composition of the company includes: 74.81% from media culture products and solutions, 17.56% from automotive intelligent cockpit products, 7.42% from industrial and satellite products and solutions, and 0.21% from other sources [1] Shareholder Information - Among the top ten circulating shareholders of Donghong Technology, one fund from GF Fund Management, the GF Technology Innovation Mixed A (008638), entered the top ten in the second quarter, holding 1.8713 million shares, which accounts for 1.67% of the circulating shares. The estimated floating loss today is approximately 5.1836 million CNY [2] - The GF Technology Innovation Mixed A fund was established on December 25, 2019, with a latest scale of 2.657 billion CNY. Year-to-date returns are 49.37%, ranking 1079 out of 8162 in its category; the one-year return is 66.06%, ranking 568 out of 8015; and since inception, the return is 132.17% [2] Fund Management - The fund manager of GF Technology Innovation Mixed A is Wu Yuanyi, who has been in the position for 5 years and 16 days. The total asset scale of the fund is 20.478 billion CNY, with the best fund return during the tenure being 111.57% and the worst being -15.85% [3]

Core Viewpoint - The recent financial report of Danghong Technology (688039) shows a positive trend in revenue and profit margins, indicating improved operational efficiency and potential growth opportunities in various business segments [1]. Financial Performance - Total revenue for the first half of 2025 reached 133 million yuan, a year-on-year increase of 12.7% [1]. - The net profit attributable to shareholders was -6.15 million yuan, showing an improvement of 85.27% compared to the previous year [1]. - In Q2 2025, total revenue was 83.9 million yuan, up 50.44% year-on-year, with a net profit of 5.74 million yuan, an increase of 130.65% [1]. - Gross margin improved to 42.21%, a year-on-year increase of 26.44%, while net margin improved to -7.17%, up 81.59% [1]. - The total of selling, administrative, and financial expenses was 35.65 million yuan, accounting for 26.81% of revenue, a slight increase of 4.76% year-on-year [1]. Key Financial Metrics - Earnings per share improved to -0.05 yuan, an increase of 86.49% year-on-year [1]. - Operating cash flow per share was 0.0 yuan, reflecting a 100.53% increase year-on-year [1]. - The company's cash and cash equivalents decreased by 40.64% to 86.93 million yuan due to operational expenditures [1]. Business Segments - The AI products and multimodal large model derivatives have rapidly applied in the market, particularly boosting the media culture business and in-vehicle intelligent cockpit business [8]. - The smart connected vehicle business is expected to grow significantly as demand for in-cabin multimodal interaction and intelligent entertainment cockpit experiences increases [12]. - The industrial and satellite business focuses on intelligent video analysis and data mining applications, enhancing capabilities in high-precision inspections and real-time satellite remote sensing [13]. - The media culture business is evolving from a hardware supplier to a comprehensive intelligent video ecosystem service provider, capitalizing on opportunities in the ultra-high-definition video industry [13].

Core Viewpoint - Hangzhou Donghong Technology Co., Ltd. has officially launched the BlackEyeVision robot ultra-long-distance remote control system, marking a significant advancement in commercializing ultra-low latency remote control solutions in China [1][2] Group 1: Technology Breakthroughs - The BlackEyeVision system is built on three major technological breakthroughs, addressing key pain points in remote robot control [1] - The self-developed frame-level encoding technology achieves ultra-low latency transmission within 80 milliseconds, surpassing the human neural response limit by 20 milliseconds [1] - The system utilizes the BlackEye multimodal audiovisual model, providing video compression capabilities of 10 to 100 times, ensuring high-definition video transmission even in narrow bandwidth environments [1] Group 2: System Capabilities - The system can simultaneously process multimodal data, including video, audio, LiDAR, images, signaling, and text, enabling intelligent extraction of key information and environmental semantic understanding [1] - It supports AI empowerment at the edge, enhancing the overall functionality of the remote control system [1] Group 3: Application and Future Plans - The system has been applied in both pre-installed and retrofitted forms in products like robotic dogs and inspection robots, demonstrating effectiveness in emergency rescue and industrial inspection scenarios [2] - The company plans to expand the application of the BlackEyeVision system to lighter scenarios, such as home environments, enabling real-time interaction and remote control [2] - The launch of the BlackEyeVision system represents the company's first step into the robotics field, with ongoing efforts to promote the implementation and innovation of intelligent video technology across various scenarios [2]