9月24日—26日，2025年中国国际信息通信展览会（PT展）在北京国家会议中心举行。本次PT展上，诺基亚贝尔带来了基于AI智能体的网络自智运维解决方 案。展台上，"迈向L5完全自智"的标识引人驻足。 诺基亚贝尔云网服务事业部自智网络负责人王琳对21世纪经济报道记者表示，自智网络从level 0到level 5代表着从全人工值守到完全无人值守的演进，目前 中国的运营商大概达到了Level 3.5，部分场景实现Level 4，即仍然需要人工进行监督检查。公司此次带来的便是推进自智网络走向完全自智的愿景、方案， 主要包含四大关键路径，一是可信的AI-Ready数据，可以实现从保障数据质量到为AI组织数据；二是可度量的全自动流程，对运营模式进行充分变革，打通 流程中的断点；三是可进化的聪明Agents，它可推理可行动，还能在工作中自主学习，进行准确的意图管理；四是可推演的"网络孪生"，可通过全息拓扑实 时反映网络状态。"这四点是帮助运营商实现全智能的、无人值守的网络的核心"。 21世纪经济报道见习记者冉黎黎 北京报道 ...

Financial Performance - In the first half of 2025, the company achieved operating revenue of 106.04 million yuan, a decrease of 19.16% compared to the same period last year [2][3] - The net profit attributable to shareholders was -43.04 million yuan, down 85.70% year-on-year [3] - The net profit after deducting non-recurring gains and losses was -44.06 million yuan, a decline of 71.40% compared to the previous year [3] Business Challenges - The decline in software development orders due to telecom operators' cost-cutting strategies negatively impacted revenue targets for the first half of 2025 [3] - The company is actively advancing the development of the next-generation OSS product platform to create more business opportunities [3] Project Updates - The Zhengzhou Airport computing power project is progressing steadily, with equipment procurement and network testing underway [4] - The project is expected to generate new business income over a five-year operational period once completed [4] Strategic Direction - The company maintains a clear operational strategy, focusing on customer value and integrated marketing efforts [4] - New projects, including the Zhengzhou Airport Intelligent Computing Center, are being executed, with significant progress in product development [4] Capital Raising - The company has initiated a private placement for 2024, pending approval from the Shenzhen Stock Exchange and the China Securities Regulatory Commission [6]

Core Insights - The launch of the all-domain integrated computing network scheduling platform and the first wide-area network model and multi-agent system marks a significant advancement in China's computing resource management and network operations [1][2] - The platform aims to connect regions with abundant computing resources to those with high demand, potentially reducing management costs for enterprises by 50% [1] - The AI automatic design toolchain for baseband circuits is expected to streamline the design process, reduce costs, and improve efficiency in communication systems [2] Group 1 - The all-domain integrated computing network scheduling platform utilizes three pioneering technologies to achieve integrated scheduling across the nation [1] - The platform has been tested in various sectors, including hospitals and schools, and is aligned with national initiatives like "East Data West Computing" [1] - The wide-area network model and multi-agent system can autonomously sense, maintain, and repair network issues, applicable in 27 typical network operation scenarios [1][2] Group 2 - The system, led by the Purple Mountain Laboratory in collaboration with Jiangsu Future Network Group, China Unicom, and Huawei, has achieved an overall intelligence capability level of L4 [2] - The goal is to reach L5 level, enabling a fully self-intelligent network that can be generated on demand [2] - The AI automatic design toolchain can reduce the area of baseband circuits by 70% while maintaining communication performance, significantly shortening the design iteration process to just a few hours [2] Group 3 - The advancements in baseband circuit design are expected to lower energy consumption and costs for enterprises, ultimately benefiting consumers with improved product performance at reduced prices [3]

Performance Forecast - The company expects a net loss attributable to shareholders of 40 million to 46 million yuan for the current reporting period, compared to a loss of 23.1757 million yuan in the same period last year [1] - The net loss after deducting non-recurring gains and losses is projected to be between 41 million and 47 million yuan, compared to a loss of 25.7039 million yuan in the previous year [1] - The basic earnings per share are expected to be a loss of 0.39 to 0.45 yuan per share, compared to a loss of 0.23 yuan per share in the same period last year [1] Communication with Auditors - The company has communicated with the accounting firm regarding the performance forecast and there are no discrepancies between the company and the auditors concerning the performance forecast [1] Reasons for Performance Variance - The company's operating income shows significant seasonality, with a higher proportion in the fourth quarter, while management, sales, and R&D expenses are incurred more evenly throughout the quarters, leading to losses in the first half of 2025 [1] - The decline in software development business orders due to telecom operators' cost-reduction strategies has impacted the revenue targets for the first half of 2025 [1] - The company is actively advancing the development of the next-generation OSS product platform to create more business opportunities for incremental revenue in OSS [1] - In the new computing power business, the company is in a rapid development phase, with related projects progressing orderly towards operational status to gradually realize revenue [1]

Core Insights - Huawei's data center autonomous network achieved an overall intelligence level of AN L3.9, with core business scenarios in "planning and configuration" and "application deployment and configuration" reaching AN L4 level, marking it as the first solution to pass EANTC L4 autonomous network testing [1][2] - The evaluation by EANTC, a recognized independent network testing organization, serves as a significant reference for assessing network product performance, reliability, and intelligence level [2] Group 1 - The autonomous network grading assessment focused on three key value scenarios: planning and configuration, application deployment and issuance, and monitoring and troubleshooting, analyzing four critical capabilities of autonomous networks [2] - Huawei's solution demonstrated high intelligence and reliability in data center network operations, aligning well with the goals of AN L4, especially as enterprises expand data centers due to AI/ML workloads and private cloud adoption [2][3] Group 2 - The autonomous network solution has been deployed at scale in industries such as finance and the internet, with plans for broader implementation across various sectors in collaboration with industry organizations and testing agencies [3]

Core Viewpoint - The global telecommunications industry is facing a "growth without revenue" bottleneck, where the increase in network traffic does not translate into corresponding revenue growth, leading to a "growth reduction" phenomenon [1][3]. Group 1: Industry Challenges - The traditional network service model is homogenized, failing to meet diverse market demands, resulting in a lack of differentiation between high-value and ordinary services [1]. - Operators are experiencing a "pipeline" dilemma, where the expansion of 5G networks does not yield proportional income increases [1]. Group 2: Differentiated Connectivity - "Differentiated connectivity" has become a consensus in the industry, focusing on using technology to identify the value of different services and providing customized network guarantees for high-priority applications [3]. - Singapore Telecommunications (Singtel) exemplifies this approach by offering tiered service packages based on user needs, transforming operators from mere traffic providers to "service value definers" [3]. Group 3: Programmable Networks and AI Integration - Ericsson views programmable networks as a core development goal for 5G-A, enabling dynamic network configuration based on business needs through software-defined networking (SDN) and network function virtualization (NFV) [5]. - The integration of AI is reshaping network management, transitioning from passive to proactive management, with AI acting as a "network brain" for autonomous decision-making [5][7]. Group 4: Ecosystem Development - Ericsson is building an open ecosystem to attract third-party developers, creating a "network as a service" economic model, with a RAN ecosystem comprising 56 members [8]. - The acquisition of Vonage and the establishment of Aduna aim to create a CPaaS ecosystem, addressing fragmentation in network capability and enhancing collaboration with developers [8]. Group 5: Future Outlook - Despite the commercial launch of 5G-A, challenges remain, including deployment strategy delays in some regions and low penetration rates of new terminals [9]. - Ericsson proposes a dual-track development strategy to enhance 5G-A capabilities while promoting end-to-end differentiated services, aiming to redefine the telecommunications industry's revenue model and digital infrastructure [9].

Core Insights - Huawei has been awarded the "Data Center Intelligent Network Basic Capability Solution Testing Certificate," marking a significant milestone in the development of intelligent network technology [1][2] - The certification validates Huawei's technical capabilities in L4 intelligent networks for data centers, setting a new technical benchmark in the industry [2] Group 1: Certification and Evaluation - The China Academy of Information and Communications Technology (CAICT) issued the certification to Huawei and other companies, confirming their capabilities in intelligent networks [1] - CAICT, in collaboration with industry partners, developed the "Intelligent Network Basic Capability Grading Assessment Testing Method - Data Center Network (2023 Edition)," which defines L1 to L4 grading capabilities and testing methods across three major value scenarios [1] Group 2: Performance and Applications - Huawei's intelligent network solution excelled in three key scenarios: intelligent deployment of POD, intelligent application access initiation, and intelligent fault handling, demonstrating capabilities such as automatic generation of optimal deployment plans and precise fault prediction [1][2] - The solution enhances operational efficiency for industries like finance by providing self-generating configurations and self-diagnosing faults [2] Group 3: Future Developments - Huawei plans to continue increasing R&D investment and collaborate with industry partners to advance intelligent network technology, contributing to the construction of smart, efficient, and reliable ICT infrastructure for digital transformation [2]