分布式智能云
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连续4年!浪潮云入选Gartner中国云基础设施和平台服务市场标杆厂商
Da Zhong Ri Bao· 2025-09-23 06:25
近日,国际权威IT研究与咨询顾问机构Gartner正式发布《Market Guide for Cloud Infrastructure and Platform Service in China》报告,浪潮云凭借在分布式云、混合云/私有云等领域的突出表现,连续4年 作为标杆厂商入选。 报告通过选取中国典型的云基础设施和平台服务提供商,为决策者提供市场指南性参考。报告指出,通 过搭乘生成式人工智能发展潮流,云服务提供商正将重点放在人工智能/机器学习(ML)、生成式人工 智能基础设施投资、大数据及其他增值服务上,以寻求新的市场机遇。 当前,人工智能作为引领新一轮科技革命和产业变革的颠覆性技术,已成为国际竞争的新焦点和经济发 展的强大引擎。作为智慧系统的全场景运营商,浪潮云积极响应"人工智能+"行动部署,面向组织用 户,打造分布式智能云,完整构建起智数云安一体化融合的发展路径,并基于Powered By模式,依托云 舟联盟和海若智能体生态伙伴形成全场景生态价值链,打通组织智能化落地"最后一公里"。 Gartner在报告中指出,私有云解决方案能够为企业提供一种构建更灵活基础设施服务的方式,以满足 不同需求。为此,浪潮 ...
浪潮云两案例入选IDC中国数据空间市场最佳实践
Huan Qiu Wang Zi Xun· 2025-05-28 06:14
Core Insights - The IDC report highlights the current challenges and scenarios in data space construction, predicting rapid growth in the urban data space market by 2025 due to government initiatives for data resource integration and sharing [1][2] Group 1: Data Space Market Analysis - Data space is defined as an operational model focusing on control capabilities, typically constructed by one or more entities based on business needs [1] - The report emphasizes that despite being in an exploratory phase, the urban data space market is expected to expand significantly by 2025 [1] Group 2: Company Initiatives - Inspur Cloud has actively explored various data space constructions, leveraging distributed intelligent cloud technology to create trusted data space products [1][3] - The company provides distributed data infrastructure services that support the entire lifecycle of data collection, calculation, and utilization, addressing security and trust issues among participants [1][2] Group 3: Case Studies - The Jinan Trusted Data Space, developed with the Jinan Big Data Bureau, integrates services like digital identity, privacy computing, and data authorization to enhance data utilization and drive digital transformation [2] - In the electricity sector, Inspur Cloud has built a trusted data space to manage the entire lifecycle of power data, facilitating intelligent operations and improving power supply-demand balance through advanced analytics [2] Group 4: Future Directions - The report suggests that technology providers should focus on privacy computing and gradually create a data industry ecosystem, leveraging large models within data spaces [3] - Inspur Cloud aims to accelerate the application of data elements and promote the widespread implementation of trusted data spaces through innovative models [3]
浪潮云肖雪:以“分布式智能云”化解智能化落地难题
Zhong Guo Jing Ji Wang· 2025-03-25 16:38
Core Viewpoint - The article discusses the launch of Inspur Cloud's "Distributed Intelligent Cloud" strategy, aimed at addressing the challenges of implementing artificial intelligence in organizations, emphasizing the importance of a comprehensive and sustainable approach to cloud services and AI integration [1][2]. Group 1: Strategic Vision - Inspur Cloud aims to become a "full-scenario operator of intelligent systems," promoting the vision of "intelligence everywhere with cloud" to enhance AI application across various sectors [2][3]. - The company emphasizes the need for a unified, one-stop intelligent architecture to facilitate the practical application of AI technologies [2]. Group 2: Technological Development - The strategy includes upgrading all existing distributed cloud nodes to distributed intelligent cloud nodes within six months, with a target of exceeding 1,000 nodes by the end of the year [1]. - Inspur Cloud has developed a dual-engine public service platform, DeepSeek and HaiRuo, to continuously provide model capabilities and support the deployment of over a hundred intelligent agents tailored to organizational needs [3]. Group 3: Market Positioning - Since entering the cloud service sector in 2011, Inspur Cloud has evolved from a government cloud system integrator to a distributed cloud service provider, focusing on industry cloud, data cloud, and large model strategies over the past five years [1]. - The company positions itself as an operator capable of addressing the operational challenges associated with localized deployment of large models, offering diverse cloud deployment options [3].