Nvidia(US:NVDA) Zhong Guo Jing Ji Wang·2025-11-24 09:05Core Insights - The article discusses the intense AI arms race led by major tech companies like Microsoft and Google, which have invested a total of $380 billion in key infrastructure such as data centers and AI chip development this year [1] - Despite the aggressive expansion, market sentiment is shifting, highlighted by Nvidia's stock volatility, which saw a drop of 3.9% on November 4, resulting in a market value loss exceeding 1.4 trillion RMB [1][3] - The article raises concerns about whether the massive investments in AI are creating a new bubble and the potential for a chain reaction if fear spreads among investors [1] Group 1: Nvidia's Influence on the Market - Nvidia's stock price fluctuations are now seen as a barometer for the entire U.S. stock market, with its third-quarter revenue exceeding expectations leading to a market rally, while subsequent sell-off announcements from major institutions caused significant declines [3] - Analysts indicate that the U.S. stock market has become overly reliant on a few leading companies like Nvidia to deliver strong earnings for overall market stability, suggesting a deviation from healthy market dynamics [3] Group 2: AI Bubble Risks - Historical patterns show that market bubbles often arise from value deviation, emotion-driven behavior, and risk accumulation, with the current AI arms race contributing to these risks [5] - Goldman Sachs predicts that capital expenditures for leading AI firms will reach $1.4 trillion between 2025 and 2027, with over $400 billion expected in 2025 alone, yet many companies, including OpenAI, are experiencing significant losses [5] - The U.S. tech sector is developing a "debt-driven growth" model, with over $200 billion in AI-related bonds expected to be issued by 2025, creating a potentially risky financial cycle [5] Group 3: China’s Position in the AI Landscape - There are notable differences in valuation and development paths between the U.S. and China in the AI sector, with Chinese companies being viewed as undervalued compared to their U.S. counterparts [7][8] - The U.S. focuses on a "technology-driven" approach, heavily investing in general artificial intelligence (AGI), while China adopts a more pragmatic "application-driven" strategy, emphasizing the synchronization of technology deployment and commercial returns [8] - China's advancements in AI chips, open-source ecosystems, and industry applications position it to withstand external risks and potentially gain a favorable position in the global AI industry restructuring [8]