AI DC白皮书

Industry Investment Rating - The report highlights the transformative potential of AI, particularly in the context of AI-driven data centers (AI DC), which are becoming the core infrastructure for enterprises aiming to achieve intelligent transformation [5][6][9] Core Viewpoints - AI is an irreversible trend, not a passing trend, and it will reshape every industry and organization [4][22][23] - The future of data centers is defined by AI, with AI DC being a comprehensive reconstruction of traditional data centers, shifting from cost centers to innovation centers [5][6][46] - AI DC will play a critical role in supporting AI model training, inference, and application, becoming the cornerstone of enterprise intelligent transformation [5][6][9] Chapter Summaries Chapter 1: AI World Vision and Macro Drivers - AI is a major direction that cannot be stopped, with generative AI and large models driving a new industrial revolution [16][18] - The global AI market is rapidly expanding, with significant investments in generative AI, despite a slight decline in overall AI investment [16] - AI is expected to trigger a once-in-a-century transformation, reshaping industries and driving economic growth [18][20] Chapter 2: All in AI - Generative Business Systems - Enterprises face both uncertainties and certainties in adopting AI, with over 70% of leaders expecting AI to significantly impact their business within five years [29] - The key to successful AI adoption lies in building an enterprise-level AI architecture that can handle the instability of large models and the "impossible triangle" of generalization, specialization, and economy [31][33] - Enterprises should focus on application scenarios, data, models, and computing power to achieve value creation and business transformation [34][36] Chapter 3: Development and Changes in Data Centers - Data centers are evolving into AI DC, which are designed to support AI model training, inference, and application, with a focus on high-performance computing and energy efficiency [49][51] - AI DC differ from traditional data centers in terms of business load, computing power type, and cooling methods, with a shift towards xPU-centric architectures and liquid cooling [51][52] - AI DC are categorized into three types: ultra-large, large, and small, each serving different needs and facing unique challenges [56][57][58] Chapter 4: Typical AI DC Planning and Construction - Ultra-large AI DC are primarily used for foundational model pre-training, facing challenges such as power supply, reliability, and effective computing power [59][60] - Large AI DC are used by industry leaders for secondary training and central inference, with a focus on optimizing inference performance and resource utilization [60] - Small AI DC are designed for lightweight inference and AI applications, requiring flexible deployment, easy maintenance, and security [61][62] Chapter 5: AI DC Construction and Development Initiatives - The report proposes four key initiatives for AI DC development: moderate超前 construction, intensive and green development, open collaboration, and building three foundational bases to accelerate AI adoption [15] - AI DC will be redefined by AI, providing diverse computing power and enabling the innovation of AI-native applications [47][65]