[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fjx6xyfoRy72b-5lfoj_IK6H551HAgP6WG7paySR60GY":3},{"code":4,"msg":5,"data":6},200,"操作成功",{"id":7,"title":8,"content":9,"digest":10,"source":10,"coverPath":11,"thumbsCoverPath":12,"isTop":13,"isShow":14,"baseClick":13,"clickCount":15,"createTime":16,"typeId":17,"isNewest":18,"newsInfoTypeRespVo":19,"voiceUrl":22,"voiceSize":23,"taskId":24,"releaseTime":25,"titleEn":26,"contentEn":27,"voiceUrlEn":28,"taskIdEn":29,"voiceSizeEn":30},1449,"思科推出全新统一边缘平台，赋能分布式代理型AI工作负载","\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">11月4日，思科在全球合作伙伴大会（Cisco Partner Summit）上宣布推出思科统一边缘（Cisco Unified Edge）解决方案。\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">据悉，这是一款面向分布式AI工作负载的集成计算平台，能够将数据中心的强大算力与规模扩展至边缘，支持在数据生成源地实时运行AI应用与推理。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2026\u002F03\u002Fhistory\u002F2b88d9bf49e14a11830d45a09e7e3a48.png\" width=\"null\" height=\"null\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">当前，超过半数的AI试点项目因基础设施限制而停滞，凸显出对新型去中心化网络架构的迫切需求。今年预计有75%的企业数据将在边缘创建和处理，边缘计算已成为新的AI前沿阵地。随着AI工作负载从集中式模型训练加速转向实时推理，传统数据中心已难以满足需求。AI代理正彻底改变网络流量模式，从可预测的突发模式转变为持续不断强度负载。其中，代理型AI查询所产生的网络流量最高可达聊天机器人的25倍。相比传统数据中心双向传输数据的模式，AI工作负载要求模型和基础设施部署在更接近数据生成与决策的位置。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">“当前的基础设施已经无法满足大规模AI应用的需求。随着AI代理和应用的广泛应用，它们自然会出现在更靠近客户交互和决策制定的地方——无论是分支办公室、零售店、工厂车间还是体育场等。这些正是计算能力应该部署的地方。”思科全球总裁兼首席产品官Jeetu Patel表示，通过统一边缘平台，思科为企业提供了灵活、安全的系统，易于部署、操作并随需求增长而扩展，帮助他们在现实世界中轻松部署AI。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">据悉，思科统一边缘解决方案支持从边缘到核心的实时推理和代理型工作负载，帮助企业从容实现大规模AI部署与管理。该设计具有可扩展性与适应性，无需大规模替换升级即可应对未来需求，不仅可以保护现有的AI投资，也能支持尚未出现的应用场景和服务。其还具有以下几大特点：\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· 赋能实时AI的出色性能与模块化设计：\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">全栈融合架构将计算、储存甚至网络整合到单一平台，并由广泛的合作伙伴生态系统支持。模块化机箱可灵活配置CPU和GPU，具备冗余电源与散热、高性能SD-WAN网络以及与经过验证的设计，以支持当前的应用和未来的创新场景。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· 从边缘到核心的运维简化：\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">零接触部署和经过预验证的蓝图使AI的部署更快速、更可预测。通过思科Intersight进行集中管理，并结合自动化的全域运维，简化了扩展、故障排查和升级过程，无需现场专业技术人员。借助与 Splunk 和 ThousandEyes 的集成，客户能够获得端到端的可观测性，实现大规模的边缘管理。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· 为边缘AI内置安全：\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">多层零信任安全架构在每个层面保护AI环境。防篡改功能、深度遥测、一致的安全策略以及稳定的配置保障了系统的韧性；而审计追踪则在运营扩展时保障合规性。安全内置于设备中，并可将零信任原则应用于每一次访问、分段及AI应用与模型的保护。这种方法应对了边缘侧不断扩大的攻击面，帮助防御物理和网络威胁，确保AI运行安全。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">思科方面介绍，他们与零售、制造、金融服务和医疗等行业的客户紧密合作，共同设计出适应现实世界复杂性和限制的平台。这意味着该平台既要支持当今的传统工作负载，也需应对未来庞大的AI工作负载。企业需要在管理当前的实时应用（由CPU支撑）与未来需要GPU的AI密集工作负载之间找到平衡。客户的反馈直接影响了平台的架构设计、部署方式、安全管理和大规模运维方案。无论是在生产车间运行AI工作负载，还是在银行分支机构提供安全数字服务，该平台都能支持关键场景下的实时决策。目前，思科统一边缘平台已开放订购，预计将于今年年底全面上市。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】数智前线 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20251104A057RK00#\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FRH7anFgRokfIkEqKFt6gTg\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（本网转发此文章，旨在为读者提供更多的信息资讯，所涉内容不构成投资、消费建议。文章事实如有疑问，请与有关方核实，文章观点非本网观点，仅供读者参考。）\u003C\u002Fspan>\u003C\u002Fp>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F11\u002F694c27cfa1d14f36bf5513b53e86ec4f\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F11\u002Fthumbs\u002F694c27cfa1d14f36bf5513b53e86ec4f\u002FAI领域.jpg",0,1,50,"2025-11-10 16:34",2,false,{"id":17,"name":20,"enName":21},"芯位视野","Xinwei Vision","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3Aaa9ce4b1-ed20-4507-8caf-0610b04dea4c%3A0.wav?Expires=1762824675&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=ik%2F%2BRYe5rG8H%2Bv9v94L%2F%2BonfEcY%3D",7664346,"aa9ce4b1-ed20-4507-8caf-0610b04dea4c","2025-11-11 08:00","Cisco Launches New Unified Edge Platform to Empower Distributed Agent-Based AI Workloads","\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">On November 4, Cisco announced the launch of the Cisco Unified Edge solution at the Cisco Partner Summit.\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">It is an integrated computing platform designed for distributed AI workloads, capable of bringing the power and scalability of data centers to the edge, supporting real-time AI applications and inference at the data generation source.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2026\u002F03\u002Fhistory\u002F2b88d9bf49e14a11830d45a09e7e3a48.png\" width=\"null\" height=\"null\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Currently, over half of AI pilot projects are stalled due to infrastructure limitations, highlighting the urgent need for a new decentralized network architecture. It is expected that 75% of enterprise data will be created and processed at the edge this year, making edge computing the new frontier for AI. As AI workloads shift from centralized model training to real-time inference, traditional data centers are struggling to meet the demand. AI agents are fundamentally changing network traffic patterns, shifting from predictable burst patterns to continuous high-load traffic. The network traffic generated by agent-based AI queries can be as high as 25 times that of chatbots. Compared to the traditional two-way data transmission mode of data centers, AI workloads require models and infrastructure to be deployed closer to where data is generated and decisions are made.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">“Current infrastructure is no longer sufficient to meet the demands of large-scale AI applications. With the widespread adoption of AI agents and applications, they naturally appear closer to customer interactions and decision-making locations—whether it's branch offices, retail stores, factory floors, or stadiums. These are precisely the places where computing power should be deployed,” said Jeetu Patel, President and Chief Product Officer of Cisco. Through the unified edge platform, Cisco provides enterprises with a flexible and secure system that is easy to deploy, operate, and scale with demand, helping them easily deploy AI in the real world.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">According to reports, the Cisco Unified Edge solution supports real-time inference and agent-based workloads from the edge to the core, helping enterprises achieve large-scale AI deployment and management. This design is scalable and adaptable, able to meet future needs without major replacements or upgrades, protecting existing AI investments while also supporting scenarios and services yet to emerge. It has the following key features:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· Excellent Performance and Modular Design to Empower Real-Time AI:\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">The full-stack integrated architecture combines computing, storage, and even networking into a single platform, supported by an extensive partner ecosystem. Modular chassis allows flexible configuration of CPUs and GPUs, featuring redundant power and cooling, high-performance SD-WAN networks, and verified designs to support current applications and future innovation scenarios.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· Simplified Operations from Edge to Core:\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">Zero-touch deployment and pre-validated blueprints make AI deployment faster and more predictable. Centralized management through Cisco Intersight, combined with automated global operations, simplifies scaling, troubleshooting, and upgrades, without requiring on-site technical experts. By integrating with Splunk and ThousandEyes, customers gain end-to-end observability, enabling large-scale edge management.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: rgb(255, 153, 0); font-size: 18px;\">· Built-in Security for Edge AI:\u003C\u002Fstrong>\u003Cspan style=\"font-size: 18px;\">A multi-layer zero-trust security architecture protects the AI environment at every level. Tamper-proof features, deep telemetry, consistent security policies, and stable configurations ensure system resilience; audit trails ensure compliance during operational expansion. Security is built into the device and the zero-trust principle is applied to every access, segmentation, and protection of AI applications and models. This approach addresses the expanding attack surface at the edge, helping defend against physical and network threats, ensuring safe AI operations.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Cisco mentioned that they have closely collaborated with customers in industries such as retail, manufacturing, financial services, and healthcare to design a platform that adapts to the complexity and constraints of the real world. This means the platform must support today's traditional workloads while also addressing future massive AI workloads. Enterprises need to find a balance between managing current real-time applications (supported by CPUs) and future AI-intensive workloads requiring GPUs. Customer feedback directly influenced the platform's architectural design, deployment methods, security management, and large-scale operations. Whether running AI workloads in production workshops or providing secure digital services at bank branches, the platform supports real-time decision-making in critical scenarios. Currently, the Cisco Unified Edge platform is available for order and is expected to be fully launched by the end of this year.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source] Shuzhi Qianxian \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20251104A057RK00#\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FRH7anFgRokfIkEqKFt6gTg\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reprinted by this site to provide readers with more information and news. The content does not constitute investment or consumption advice. If there are any questions about the facts in the article, please verify with the relevant parties. The views in the article are not those of this site and are for reference only.)\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3Aea8c2a95-5638-4e7c-895d-f27d8f407f42%3A0.wav?Expires=1774838454&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=TX1tcMEDO5k385BHx8BizDo78sI%3D","ea8c2a95-5638-4e7c-895d-f27d8f407f42",9180228]