Nvidia(US:NVDA) Ge Long Hui·2025-11-25 08:39Core Viewpoint - The increasing probability of a Federal Reserve rate cut has led to a significant rebound in Chinese and American tech stocks, particularly in the AI hardware sector, which has driven the A-share market upward. Additionally, 16 new hard technology funds have been approved for sale, including the first AI-focused ETF tracking the "Innovation and Entrepreneurship AI Index" set to launch on November 28, 2025 [1][5]. Group 1: AI Index Overview - The "Innovation and Entrepreneurship AI Index" was established on May 14, 2025, after extensive research on the AI industry, selecting 50 stocks from the STAR Market and the ChiNext that focus on the AI supply chain [2]. - The index emphasizes two key sectors: communication equipment (37.92%) and semiconductors (31.21%), which together account for nearly 70% of the index, highlighting a focus on AI infrastructure [2][4]. - The index has outperformed other AI indices, with a year-to-date increase of 73% as of November 24, surpassing the ChiNext AI index (69.36%) and others like CS AI (49.14%) and Innovation and Entrepreneurship AI (41.91%) [4]. Group 2: Market Dynamics and Challenges - Recent volatility in global tech stocks reflects liquidity issues and market skepticism regarding the AI narrative, particularly following Nvidia's rise to a $50 billion market cap, raising concerns about the authenticity of AI demand [8]. - Analyst Ming-Chi Kuo refuted claims of Nvidia's financial misconduct, arguing that the increase in accounts receivable turnover days (DSO) is reasonable given the concentration of major clients [8]. - The market's perception of Nvidia's inventory increase (32% quarter-over-quarter) is challenged by Kuo, who suggests it aligns with production trends and indicates strong demand for new products [8]. Group 3: Competitive Landscape - Google's TPU is seen as a potential threat to Nvidia's GPU dominance, with reports of significant investments from companies like Meta in TPU technology [11]. - TPUs are designed for specific tensor computations, offering higher energy efficiency compared to GPUs, which are versatile but less specialized [13][14]. - Despite the emergence of TPUs, Nvidia's strong software ecosystem, including the CUDA platform, and its established market position provide significant competitive advantages that are not easily disrupted [16][17].