3 6 Ke·2025-10-19 10:16Core Viewpoint - The article argues that the current state of artificial intelligence (AI) is not a bubble, but there are potential danger signals that need to be monitored through a framework of five indicators [1][2][6]. Group 1: Definition and Historical Context of Bubbles - Bubbles are not just financial phenomena but also cultural products, often associated with greed and folly [7]. - Historical examples of bubbles include the South Sea Bubble, the Roaring Twenties stock market, and the 2008 housing market crash, each characterized by overvaluation and subsequent collapse [9][10]. - The article defines a bubble as a situation where stock values drop by 50% from their peak and remain low for at least five years [10][13]. Group 2: Current AI Investment Landscape - Since the launch of ChatGPT, capital expenditures by large-scale cloud service providers have more than doubled, raising questions about the sustainability of such spending [14][16]. - Morgan Stanley predicts that AI infrastructure spending will reach $3 trillion by 2029, indicating significant investment momentum [17]. Group 3: Five Indicators Framework - The five indicators to assess the AI landscape are: 1. Economic Pressure: Evaluates whether current investment levels are distorting the economy [18]. 2. Industry Pressure: Assesses if industry revenues align with capital expenditures [30]. 3. Revenue Growth: Measures the speed of revenue growth relative to investment [35]. 4. Valuation Heat: Analyzes how high valuations are compared to historical standards [39]. 5. Quality of Capital: Examines the source and structure of funding supporting the industry [46]. Group 4: Economic Pressure - Current AI investment is at approximately 0.9% of U.S. GDP, projected to rise to 1.6% by 2030, indicating it is currently in the green zone but may soon enter the yellow zone [23][27]. Group 5: Industry Pressure - The capital expenditure to revenue ratio for generative AI is currently six times, indicating significant pressure, but this is not yet a warning sign as demand for AI services remains high [33]. Group 6: Revenue Growth - Generative AI revenue is expected to grow significantly, with estimates suggesting it could reach $1 trillion by 2028, indicating strong growth potential [38]. Group 7: Valuation Heat - Current market valuations are not as extreme as during the internet bubble, with the Nasdaq's P/E ratio around 32, which is lower than the peak of 72 during the internet boom [42][44]. Group 8: Quality of Capital - The quality of capital in the AI sector appears stable, with major companies generating substantial cash flow to support investments, although there are concerns about future funding gaps [49][51]. Group 9: Conclusion - The analysis suggests that generative AI is in a demand-driven, capital-intensive growth phase rather than a bubble, but vigilance is required as certain indicators may signal a shift towards instability in the future [52][54].