通信专题报告：Deepseek引爆通信产业新机遇

Investment Rating - The report does not explicitly state an investment rating for the industry or specific companies. Core Insights - DeepSeek significantly reduces application costs, with training costs for DeepSeek-V3 at only 2.788 million H800 GPU hours, and input/output costs per million tokens at $0.55 and $2.19 respectively, representing a 96% reduction compared to ChatGPT O1 model [4][11][22] - The advancements in DeepSeek's algorithms and frameworks enhance inference efficiency and reduce costs, stimulating demand for AI agents across various industries [4][22] - The shift in demand for optical modules from training to inference creates new requirements for multi-scenario adaptability, particularly in distributed training and edge computing [4][42] Summary by Sections 1. Technological Breakthroughs - DeepSeek's innovative algorithms optimize reasoning efficiency and significantly lower application costs, enabling faster training and reduced GPU memory usage [4][11] - The Multi-head Latent Attention (MLA) architecture and DeepSeekMoE framework improve inference speed and memory utilization while maintaining model performance [4][13] 2. Causal Loop - The reduction in inference costs directly catalyzes the development of vertical AI agents, enhancing the demand for intelligent solutions across industries [4][22] - The integration of DeepSeek with various vertical models creates a feedback loop that optimizes the base model and reduces the need for extensive industry-specific data [22] 3. Hardware Transformation - The demand for optical modules is shifting towards inference, necessitating low-latency, high-bandwidth interconnections in data centers and edge computing environments [4][42] - The rise of edge computing and the need for distributed training are expected to increase the demand for short-distance optical modules and enhance the efficiency of communication infrastructure [4][42] 4. Vertical Model Applications - Various industries, including retail, automotive, finance, and healthcare, are leveraging DeepSeek's capabilities to enhance operational efficiency and customer experience [20][37] - The deployment of edge computing devices in sectors like industrial quality inspection and smart transportation is becoming increasingly prevalent, driven by the need for real-time data processing [37][51] 5. Network Architecture Revolution - The emergence of 5G enhanced base stations supports edge computing by providing high-speed, low-latency connections, essential for real-time data processing [29][30] - The integration of network slicing with edge computing allows for flexible resource allocation, optimizing performance for different applications [30][31]