Core Insights - The core focus of the news is on the development of a data intelligence platform by Shuxing Intelligent on Amazon Web Services (AWS), which integrates generative AI and big data processing capabilities to optimize costs and enhance data management [1][11]. Group 1: Product Overview - Shuxing Intelligent has built a comprehensive data intelligence platform on AWS, consisting of three main products: Cyber Digital Engine (SAPARINE), Cyber Data Platform (SUBDAY), and Cyber Intelligent Platform (SAIBOT AI) [2][3]. - The Cyber Digital Engine is designed to provide enterprise-level clients with a scalable and cost-optimized big data platform, utilizing AWS services like Amazon S3 for unified data storage and Amazon EKS for building native big data clusters [2][3]. - The Cyber Data Platform offers a one-stop data development and governance capability across various data architecture scenarios, including data warehouses and data lakes [3]. - The Cyber Intelligent Platform serves as a comprehensive machine learning and AI application development platform, enabling rapid deployment of AI solutions [3]. Group 2: AI and Data Synergy - The platform facilitates a bidirectional empowerment between AI applications and data management, where AI development relies on diverse structured and unstructured data, and the data platform enhances AI application efficiency [4][5]. - Shuxing Intelligent's SUBDAY product provides multi-modal data management capabilities, allowing for the collection and processing of unstructured data, thus accelerating AI application development [4][5]. - The Data Agent developed by Shuxing Intelligent automates data analysis tasks through natural language processing, significantly improving the efficiency of big data development [4][5]. Group 3: Cost Optimization Strategies - Shuxing Intelligent implements a layered optimization strategy for resource costs on AWS, achieving significant savings in service, computing, and storage costs [6][11]. - Specific measures include using object storage with hot and cold separation to reduce storage costs, employing cost-effective instance types for computing, and implementing elastic scaling strategies to optimize resource usage [6][11]. - The company reports that its optimizations can lead to a 30%-50% reduction in service resource costs, 20%-30% in computing resource costs, and 60%-80% in storage costs [6][11]. Group 4: Future Outlook - The company emphasizes the importance of transitioning from cost optimization to innovation-driven strategies in the AI era, supported by a robust data strategy and AI cloud services [12]. - Amazon plans to invest $100 billion in AI computing power and cloud infrastructure, aiming to assist Chinese enterprises in global expansion and innovation [12].