Investment Rating - The report maintains a "Recommended" rating for the electric power equipment industry [1]. Core Insights - The AI industry is transitioning from generative AI to inferential AI, with a significant increase in computational demand, approximately 1 million times over the past two years [2]. - Key performance indicators for AI factories include throughput efficiency and inference speed, with token efficiency being crucial for power efficiency [2]. - NVIDIA anticipates that the revenue from its Blackwell and Rubin flagship chip product lines will exceed $1 trillion by 2027, a significant increase from the previously projected $500 billion [2]. Summary by Sections Industry Progress - The AI industry is evolving towards inferential and intelligent AI, with inference and channel training becoming core computational demands [2]. - NVIDIA has defined 2025 as the "Year of Inference," focusing on optimizing AI inference processes and reducing infrastructure costs [2]. Product Developments - The Vera Rubin full-stack AI computing platform was officially launched, featuring several new chips and configurations [2]. - The computational power of the Vera Rubin platform is expected to increase by 40 million times over the next decade [2]. - Deployment efficiency for Vera Rubin has improved significantly, reducing installation time from two days to two hours [3]. Power Supply Developments - The cabinet power supply for the Vera Rubin NVL72 is expected to utilize four Powershelf units, each with a power capacity of 110KW, totaling 440KW, which is over 60% higher than previous models [2][3]. - NVIDIA plans to implement 800V high-voltage DC power supply systems to reduce data center PUE below 1.1 [2]. Liquid Cooling Developments - The Vera Rubin platform employs a 100% liquid cooling design, which is expected to enhance energy efficiency and reduce cooling costs [3]. - Future releases of higher power chips are anticipated to drive technological upgrades in liquid cooling solutions [3]. Investment Recommendations - Suggested companies to watch include those involved in cabinet power supplies, external power supplies, liquid cooling solutions, and data center storage [3].

Investment Rating - The report maintains a "Recommended" rating for the electric power equipment industry [1]. Core Insights - The AI industry is transitioning from generative AI to inferential AI, with a significant increase in computational demand, approximately 1 million times over the past two years [2]. - Key performance indicators for AI factories include throughput efficiency and inference speed, with token generation speed being crucial for AI intelligence [2]. - NVIDIA anticipates that the revenue from its Blackwell and Rubin flagship chip product lines will exceed $1 trillion by 2027, a significant increase from the previously projected $500 billion [2]. - The Vera Rubin full-stack AI computing platform was officially launched, featuring a substantial increase in computing power, projected to rise by 40 million times over the next decade [2]. - The power supply for the Vera Rubin NVL72 is expected to be significantly enhanced, with a total power supply of 440KW, representing an increase of over 60% compared to previous models [2][3]. Summary by Sections Industry Progress - The AI industry is evolving towards inferential and intelligent AI, with a focus on optimizing AI infrastructure costs [2]. - NVIDIA's 2025 is defined as the "Year of Inference," aiming to become the most cost-effective and reliable AI infrastructure platform globally [2]. Product Developments - The Vera Rubin platform includes multiple advanced chips and has achieved a significant reduction in deployment time from two days to two hours [3]. - The platform's cooling system utilizes 100% liquid cooling, which enhances energy efficiency and reduces cooling costs [3]. Investment Recommendations - Suggested companies to watch include: - For cabinet power: Megmeet, Euron, Newray, and others [3]. - For external power: Jinpan Technology, Igor, and others [3]. - For liquid cooling solutions: Invec, Shunling Environment, and others [3]. - For data center storage: Sungrow, CATL, and others [3]. - For backup power solutions: Yiwei Lithium Energy, and others [3].