Core Viewpoint - The article emphasizes the rapid integration of large model technology with industry applications, highlighting UCloud's commitment to building a robust AI cloud service infrastructure to support various sectors in China [1] Group 1: Infrastructure Development - UCloud is constructing two major intelligent computing centers in Inner Mongolia and Shanghai to meet the high computational demands of large model training and inference, forming a collaborative architecture of "East Data West Computing" [2] - The Ulanqab center leverages favorable climate and energy conditions to support large-scale training tasks, significantly reducing model training costs for clients [2] - The Qingpu center focuses on high-speed, low-latency inference scenarios, catering to industries like finance and brain science that require real-time processing [2] Group 2: Model as a Service (MaaS) Ecosystem - UCloud is actively building a MaaS ecosystem by collaborating with multiple model vendors and algorithm partners to create an open and compatible model marketplace, enabling one-click deployment for users [3] - The company offers an integrated large model solution for private deployment, addressing data security and compliance needs, thus lowering the technical barriers for AI application in various sectors [3] Group 3: Commitment to Independent R&D - UCloud prioritizes independent research and development as a core strategy, having established a domestic intelligent computing cluster to support the development and large-scale application of domestic large models [4] - The company promotes the "Computing Power Partner Program" to create an integrated platform for computing resource supply and service, enhancing resource utilization efficiency and making AI technology more accessible [4] Group 4: Long-term Vision for AI Integration - UCloud believes in the value of AI being applied in real-world scenarios to empower businesses, and plans to increase investment in intelligent computing infrastructure and industry solutions to drive deeper integration of AI technology [5]