Core Viewpoint - The Ninth Future Network Development Conference held in Nanjing focused on discussing future network technologies and development strategies, with significant participation from Unisplendour Corporation's H3C Group, showcasing advancements in intelligent computing networks [1][8]. Group 1: AI and Network Integration - H3C Group's Vice President Qiao Yan emphasized the need for networks to transition from passive carriers to active collaborators in the era of AI, driven by the increasing scale of AI models [3][4]. - The core concept of "computing power × connectivity" was highlighted, showcasing H3C's innovative practices in solving intelligent computing challenges through end-to-end collaboration and the DDC (Diversified Dynamic-Connectivity) architecture [3][4]. Group 2: End-to-End Collaboration - H3C's approach to end-to-end collaboration aims to optimize network performance, potentially enhancing overall computing capabilities by over 20% to 30% [4]. - The company is committed to an open ecosystem, allowing different brands and technologies to achieve optimal performance without creating a closed ecosystem [4][5]. Group 3: DDC Architecture Innovation - The DDC architecture introduced by H3C aims to decouple computing power from the network, enhancing efficiency and flexibility in accessing diverse computing resources [6][7]. - Testing by Tolly Institute showed that the DDC architecture could improve effective bandwidth by up to 107% compared to traditional protocols, demonstrating significant performance advantages [6]. Group 4: Product Launch and Future Strategy - H3C launched the new generation 800G AI computing switch H3C S9828-128EP, featuring advanced performance specifications and energy efficiency improvements of over 20% [7]. - The company aims to lead in digital solutions for the AIGC era, focusing on intelligent connectivity to empower various industries in their digital transformation [8].

8月21日下午，为期三天的第九届未来网络发展大会在南京闭幕。闭幕式上，11项未来网络领先创 新科技成果集中亮相，一批跨界合作项目签约。 本届大会围绕人工智能、大模型、数算网络等热点话题，举办开幕式、主论坛、18场分论坛，以 及未来网络领域创新成果发布、未来网络科技创新大赛、创新成果展示等活动。 大会期间，发布了全域一体化数算网调度平台、面向广域网的网络大模型与多智能体系统、基带电 路AI自动设计工具链三项具有里程碑意义的创新成果，见证了南京市数据局和拉萨市数据管理局城市算 力网"结对子"战略合作协议签约、"东数西算—未来算网协同调度联盟"第二批成员单位合作签约、"星火 计划"首批点亮城市签约，以及基于CENI的数据要素跨境流通试验示范共创行动发布等一系列具有战略 意义的合作项目签约发布。 闭幕式为未来网络领先创新科技成果举行了颁证仪式，包括《IP网络动态孪生关键技术研究与智能 运维应用》《面向人工智能调度的智算互联网络架构》《量子密话》《自主可控智算通信系统》等，涉 及量子安全、网络智能、网络孪生、算力网络等领域。 闭幕式上，还举行了紫金山实验室6G技术在智慧医疗领域的场景签约仪式，以及未来网络绿色算 网项目 ...

Group 1 - The "2025 Future Light - Future Network Technology Innovation Competition" finals were held in Nanjing, showcasing new technologies and achievements in the future network technology field [1] - The competition focused on themes such as computing-network integration, high-performance intelligent computing networks, and wide-area lossless transmission, aiming to stimulate innovation and talent development among university students [1] - A number of innovative results with both technological foresight and industrial applicability emerged from the competition, providing new ideas and solutions for the innovative development of future networks [1] Group 2 - The Tsinghua University team "OK Team" developed a general solution for network artificial intelligence, featuring a data plane deep learning inference framework that can identify malicious traffic packets [1] - The team has been researching this technology for three to four years and has created a scalable AI engine for data planes, enabling real-time network perception and intelligent decision-making [1] - The "Sakura Avenue Professional Racing Driver" team from Wuhan University focused on intelligent driving, developing a malicious attack defense system for vehicles that addresses potential security issues in autonomous driving [2] Group 3 - The competition attracted over 800 participants from more than 60 universities across China, including prestigious institutions such as Tsinghua University, Peking University, and Wuhan University [3] - The judges noted the strong relevance of the students' research directions to current cutting-edge fields, emphasizing the importance of such competitions in fostering innovation among young talents [2]

Core Viewpoint - The article discusses the challenges faced by factories in ensuring equipment safety during extreme weather conditions and highlights the shift towards digital solutions like remote operation and inspection to enhance safety and efficiency [1][3]. Group 1: Challenges in Remote Operations - Traditional manual inspection methods pose risks during high-temperature operations and are often untimely, affecting equipment safety and operational efficiency [1]. - Factories face network challenges in implementing remote operations due to network isolation for safety, remote locations, and complex environments that hinder wired connections [3]. - Existing VPN solutions are complicated and lack fine-grained access control, making them unsuitable for industries with strict compliance requirements [3]. Group 2: Solution Offered by Beirui Pugongying - Beirui Pugongying has introduced a self-developed SD-WAN technology that allows for remote networking without the need for public IPs or extensive network restructuring [5]. - The R300 series routers are designed for industrial scenarios and have achieved the highest market share in online sales for 2024 [5]. - The solution supports various industrial devices and allows for quick networking and configuration through a cloud platform, ensuring operational continuity even in extreme weather [5][7]. Group 3: Features and Benefits - The R300 series routers provide multiple link redundancy and a dual-machine hot backup mechanism to ensure continuous network operation [9]. - Beirui Pugongying's technology allows for a true local area network experience, supporting various industrial protocols and simplifying remote debugging [10]. - The visual operation and maintenance platform enhances management efficiency by providing real-time monitoring and remote batch management capabilities [12]. Group 4: Security and Compliance - The solution includes multiple security mechanisms, such as data encryption and fine-grained access control, to meet industry compliance requirements [14]. - It supports private deployment to ensure data is stored within the enterprise's internal systems, addressing the compliance needs of sectors like energy and chemicals [14].

Core Viewpoint - Ciena (CIEN) is currently rated as a Zacks Rank 5 (Strong Sell) due to a recent earnings report that missed expectations [1]. Company Overview - Ciena Corp. is a network technology company that provides hardware, software, and services to network operators, enhancing network capacity, service delivery, and automation [2]. - The company operates through several segments: Networking Platforms, Platform Software and Services, Blue Planet Automation Software and Services, and Global Services [2]. - Founded in 1992, Ciena is headquartered in Hanover, MD [2]. Earnings History - Ciena has beaten the Zacks Consensus Estimate in two of the last four quarters, but this alone does not determine its Zacks Rank [4]. - The Zacks Rank is influenced more by the movement of earnings estimates than by earnings history [4]. Earnings Estimates - Recent trends show that Ciena's annual earnings estimates have moved lower, with the current fiscal year consensus dropping from $2.46 to $2.28 over the last 60 days [5]. - The next year's estimate has also decreased from $3.36 to $3.30 in the same period [5]. - The negative movement in earnings estimates is a key reason for Ciena's Zacks Rank of 5 (Strong Sell) [5]. Market Context - Many stocks within the Zacks universe are experiencing negative earnings estimate revisions, contributing to a broader trend of stocks falling to a Zacks Rank 5 (Strong Sell) [6].

Core Insights - The 2025/2026 State of the Network study indicates that 79% of enterprise organizations are expected to increase their reliance on packet capture to enhance mean times to detection (MTTD) and resolution (MTTR) this year [1][8]. Group 1: Study Findings - The study, conducted with insights from 750 global professionals, reveals a shift towards deeper network observability and increased reliance on packet capture due to hybrid infrastructure and cloud complexity [2][9]. - Organizations with strong packet capture capabilities reported double the improvement in MTTD compared to those without, and were four times more likely to resolve issues in under an hour [3][9]. - The research highlights a 125% increase in collaborative monitoring models driven by the shift towards multi-cloud environments [9]. Group 2: Industry Trends - 42% of organizations implementing NetSecOps models reported enhanced security benefits, indicating a growing trend towards operational alignment between network and security operations [9]. - Despite challenges, 92% of organizations reported having sufficient budgets for their needs, although 78% acknowledged the necessity for more support to address rising network security threats [9]. - Investment in IT solutions is set to increase across all examined categories, reflecting a positive outlook for organizations aiming to improve uptime and operational efficiency [6].

Core Insights - G42, an AI company based in the UAE, is expanding its strategic partnership with Cisco (CSCO.O) to drive AI innovation and infrastructure development [1] - The collaboration will assess the potential for jointly developing and deploying AI-driven cybersecurity solutions [1] - The partnership is committed to exploring cooperative opportunities in key areas, including joint marketing initiatives [1]

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The white paper discusses the urgent need for high-performance networks to support the growing demands of AI and HPC, particularly in terms of scalability, stability, and performance [5][6] - It highlights the challenges faced by high-performance data center networks (HP-DCN) and high-performance wide area networks (HP-WAN) in meeting the requirements of large-scale AI model training and high-performance computing [11][23] - The report emphasizes the importance of a multi-dimensional automated operation and maintenance system to ensure network reliability and performance [17][19] - It outlines the necessity for scalable security mechanisms to protect sensitive data in increasingly large and complex network environments [21][22] Summary by Sections 1. Introduction - The introduction outlines the transformative impact of AI and HPC on network technology, emphasizing the need for enhanced network performance to support large-scale AI model training [5][6] 2. Terminology and Abbreviations - A list of relevant abbreviations and their meanings is provided, which aids in understanding the technical content of the report [7][9] 3. Key Requirements and Challenges of High-Performance Networks - **High-Performance Data Center Networks (HP-DCN)**: The report discusses the need for ultra-large-scale networking capabilities, highlighting challenges such as switch access capacity limitations and network topology constraints [11][12] - **Ultra-High Stability**: Stability is crucial for distributed systems like AI and HPC, with metrics for network availability and performance consistency being essential [13][14] - **Extreme Performance**: The report details the need for ultra-low latency, minimal jitter, and effective high throughput to maximize cluster computing efficiency [15][16] - **Multi-Dimensional Automated Operation and Maintenance**: A comprehensive monitoring system is necessary to address the complexities of AI model training networks [17][18] - **Scalable Security Mechanisms**: The report stresses the importance of integrating security into network operations to protect sensitive data [21][22] 4. High-Performance Network Technology Architecture - **Current Status and Trends**: The architecture of intelligent computing center networks is evolving, with a focus on end-to-end integration to enhance performance [26][27] - **ZTE's High-Performance Network Architecture**: ZTE's architecture aims to support ultra-large-scale, high-throughput, and low-latency networks while ensuring operational efficiency [30][31] 5. Key Technologies for High-Performance Data Center Networks - **Ultra-Large-Scale Networking Technologies**: The report discusses the need for high-capacity switches and scalable routing protocols to support large GPU clusters [36][39] - **Routing Protocols**: Various routing protocols are evaluated for their effectiveness in large-scale intelligent computing centers, with BGP and RIFT being highlighted [48][50]