Core Viewpoint - The article emphasizes the resilience and innovation of small and medium-sized enterprises (SMEs) in China, highlighting their journey through various stages of growth and the critical role of technology, particularly cloud computing, in supporting their development [1]. Group 1: Initial Stage of SMEs - SMEs in the initial stage prioritize stability and cost-effectiveness in their operations, as exemplified by Zhongyi Wulian, which provides IoT solutions for aquaculture and relies on Alibaba Cloud for server stability [5][10]. - The challenges faced by SMEs include ensuring real-time communication with clients and maintaining system reliability, especially during critical operational hours [6][10]. - The transition to cloud services, such as those offered by Alibaba Cloud, has allowed SMEs to focus on core business development without the burden of hardware management [10][11]. Group 2: Business Explosion Phase - SMEs often experience unexpected surges in demand, which can strain their backend systems, as seen with Intelligent Precision Learning's AI tutor "Hanxue Teacher," which rapidly gained popularity [14][15]. - The ability to scale operations quickly in response to increased traffic is crucial, and Alibaba Cloud's elastic computing capabilities have proven essential for managing these spikes effectively [18][21]. - Companies like Feiniqi have also leveraged cloud services to handle increased operational demands without significant changes to their application architecture [19][20]. Group 3: Technological Advancement Phase - As SMEs explore AI capabilities, they require robust support from cloud services to ensure efficient model training and deployment, as demonstrated by Intelligent Precision Learning's AI initiatives [23][26]. - The collaboration between self-built data centers and cloud services allows companies to balance flexibility and reliability, optimizing their operational efficiency [27][28]. - The advancements in Alibaba Cloud's elastic computing have enabled SMEs to innovate and reduce costs while maintaining high performance, particularly in AI applications [30][31].