According to BlockBeats, on July 20, global semiconductor stocks have generally fallen sharply recently. Securities analysts pointed out that the decline in stock prices has far exceeded the level reflected by the fundamentals.

"Even considering market concerns about the cyclical nature of the semiconductor industry, the recent stock price plunge seems excessive," said Lee Jaeman, a researcher at Hana Securities. He noted, "We believe the catalyst for a rebound in semiconductor stock prices will be the earnings reports released by US hyperscale cloud service providers starting in late July." He added, "The combined capital expenditure growth rate of Alphabet, Microsoft, Meta, and Amazon is expected to rise from 80% in the first quarter of 2026 to 83% in the second quarter and 92% in the third quarter." He further stated, "Given the increased investment demand, it is possible for semiconductor companies to maintain high operating profit margins." (Jinshi)

According to a report released by research firm Exponential View on July 20, the revenue of the artificial intelligence (AI) industry has reached a critical tipping point, indicating that the business model of technology companies investing hundreds of billions of dollars in AI infrastructure in recent years is beginning to be validated.

The report shows that AI-related sales revenue for global hyperscale cloud service providers and emerging cloud service providers has reached approximately $25 billion, exceeding the estimated depreciation costs corresponding to AI data center and chip investments for the second consecutive quarter, which are approximately $21 billion. This milestone signifies that revenue generated by the AI industry has begun to cover the cost pressures from infrastructure capital investment, and the AI economy is gradually moving from an expansion phase relying solely on capital expenditures to a revenue validation phase.

Exponential View states that current AI revenue primarily comes from AI cloud services, GPU computing power leasing, large-model APIs, enterprise AI software, and generative AI applications. As enterprise customers continue to increase their AI spending, the commercialization of AI is accelerating.

However, the report also points out that the AI industry is still far from a high-profit stage. Due to high costs of GPUs, data centers, electricity, and model development, the industry's profit margins remain limited. Current revenue is more about validating the sustainability of infrastructure investments than about generating large-scale profits.

The core competition in the next stage of the AI industry will shift from "whether there is real demand" to "which companies can achieve scalable profitability in fierce competition." As model capabilities improve and costs decrease, AI service prices may further decline, and companies will need to improve profit margins through more efficient application scenarios and business models.