Highlander(SZ:300065) Tai Mei Ti A P P·2025-08-01 07:05Group 1 - The emergence of generative AI has significantly increased the demand for computing power, transitioning from large models to intelligent agents and embodied intelligence [2] - The global AI server market is projected to grow from $125.1 billion in 2024 to $158.7 billion in 2025, reaching $222.7 billion by 2028, with generative AI servers' market share increasing from 29.6% in 2025 to 37.7% in 2028 [3] - In China, the intelligent computing power is expected to reach 1,037.3 EFLOPS by 2025 and 2,781.9 EFLOPS by 2028, with a compound annual growth rate (CAGR) of 46.2% from 2023 to 2028 [3] Group 2 - The trend of cross-domain and cross-cluster mixed training of large models is emerging, supported by advancements in computing network infrastructure [4] - The "East Data West Computing" initiative has seen over 43.5 billion yuan invested, with a total investment exceeding 200 billion yuan, improving network latency and energy efficiency [4] - The construction of computing networks is evolving towards AI-driven and distributed models, with a focus on multi-node and multi-mode collaboration [10] Group 3 - Companies face challenges in cross-cluster mixed training, particularly in integrating different computing service providers and ensuring effective communication protocols [5] - The shift in user demand from training to inference computing power is evident, indicating a transition from a scale-driven to an efficiency-driven industry [6][8] - The service model is evolving from traditional Infrastructure as a Service (IaaS) to Model as a Service (MaaS), focusing on industry-specific solutions [7] Group 4 - The increasing demand for computing power necessitates a reevaluation of self-built computing infrastructure, which may not be cost-effective for many companies [8] - Companies are increasingly opting for computing platforms to manage workloads, raising the bar for service providers to develop efficient scheduling platforms [9] - The construction of computing networks is crucial for driving innovation across various industries, with a focus on AI and distributed computing [9] Group 5 - The rise in computing demand also raises concerns about energy consumption in data centers, with AI data center capacity expected to grow at a CAGR of 40.5% by 2027 [12] - Innovative cooling technologies and strategic data center locations are being explored to reduce energy consumption [12][13] - The integration of AI technologies is enhancing the operational efficiency of data centers, leading to a shift towards fully automated "dark" data centers [15]