数据洪流下，如何重构 AI 时代的数据基础设施？

Core Viewpoint - The rapid development of AI technology is transforming data into a key driver of AI progress, necessitating a reconstruction of data infrastructure to handle the increasing complexity and volume of data types, particularly unstructured and multimodal data [1][3]. Group 1: Changes in Data Landscape - The demand for data in the AI era extends traditional needs, shifting from primarily structured data to a broader range of data types, including unstructured and semi-structured data [3]. - There is an explosive growth in data volume due to the rapid increase in AI applications, leading to a geometric increase in data scale [3]. - The way data is utilized is changing, requiring support for mixed queries that can handle various data types within a single query [3]. Group 2: Opportunities in the Data Sector - The data sector is seen as a highly certain field, with the PaaS layer acting as a crucial bridge between infrastructure and applications, indicating strong potential for growth [4]. - Companies with large amounts of unstructured data face challenges but can leverage advancements in distributed systems and large language models to convert "data debt" into valuable assets [5]. - The relationship between AI and data is bidirectional, where AI enhances data processing capabilities while high-quality data improves model accuracy [6]. Group 3: Market Dynamics and Competition - AI is reshaping traditional IT industry roles, blurring the lines between different service layers, which presents opportunities for Chinese companies to directly engage with end-users [7]. - Data companies are essentially AI companies, focusing on private data processing, which is crucial for enterprise users concerned about data security [8]. - The market may see segmentation similar to traditional databases, with opportunities across various enterprise sizes, particularly for those needing integrated solutions [9]. Group 4: OceanBase's Strategic Position - OceanBase possesses two core advantages: world-leading native distributed capabilities and an integrated architecture that can handle various workloads simultaneously [11]. - The term "data foundation" reflects a strategic repositioning to extend data processing capabilities beyond traditional definitions [13]. - OceanBase's open-source strategy aims to create a world-class open-source database, filling gaps left by slower developments in other systems [16]. Group 5: Future Outlook and Market Potential - The future vision for OceanBase is to become the data foundation for the AI era, serving millions of enterprises and helping them build robust data infrastructures [18]. - The AI market presents vast opportunities, especially in regions like Southeast Asia and South America, where infrastructure is still developing [19][20]. - The emergence of AI tools can automate services that were previously customized, providing a significant opportunity for SaaS companies to transition into product-oriented businesses [21]. Group 6: Product Developments - Recent product releases from OceanBase include enhancements in database capabilities, integration of data with AI, and the introduction of RAG services to simplify developer access to these functionalities [22]. Group 7: Industry Entry Opportunities - The current environment is favorable for new developers and entrepreneurs entering the data industry, as the intersection of data and AI is experiencing explosive growth [23].