#分享美股交易赢英伟达股票

Outperforming Nvidia in Gains, the "Seven Knights" of U.S. Stocks Make a Strong Comeback

During the internet bubble era of the 1990s, the old tech giants were hotly sought after and then lost in the wave of industry iteration. Now, riding the wave of AI infrastructure expansion, they are making a "comeback" to the center stage of capital with a "counterattack" momentum.

As of the close of U.S. stocks on June 2, the "Seven Knights" of veteran tech giants, represented by Micron Technology, Dell Technologies, Intel, Lenovo Group, Nokia, Texas Instruments, and Cisco, have seen an average stock price increase of over 170% this year, far surpassing the 5.57% average gain of the "Seven Giants" of new tech stars like Nvidia and Apple during the same period.

Why are the "Seven Knights" collectively making a comeback?

　　Why have the long-dormant tech "Seven Knights" achieved a "bend-the-curve" overtaking? To understand the logic behind the collective explosion of the "Seven Knights'" stock prices in this round, perhaps we can find the answer in the current phase of AI capital expenditure's "change" and "unchanged."

　　First, the AI mainline position remains unchanged, and global AI capital expenditure continues to expand.

　　TrendForce released a research report on the AI industry in May, raising the 2026 global capital expenditure of the nine major CSPs (cloud service providers) to $830 billion, with the annual growth rate increasing from 61% to 79%. TrendForce stated that this adjustment mainly stems from most North American CSPs recently revising upward their 2026 capital expenditure guidance in response to strong AI demand.

　　Meanwhile, as AI computing infrastructure construction advances, the allocation of funds is changing.

　　He Li, General Manager of Zhizhi Investment, pointed out to reporters that the core driver behind the recent surge in stock prices of the U.S. "Seven Knights" is the transition of AI computing infrastructure construction from "buying GPUs" to a comprehensive expansion phase of "buying everything supporting."

He Li analyzed that, from 2024 to 2025, AI investments will mainly focus on Nvidia GPU procurement and related business areas of a few cloud providers. However, after 2026, when AI data centers enter large-scale deployment, bottlenecks will spread from chips to the entire infrastructure stack, benefiting servers (Dell, Lenovo), storage (Micron), network equipment (Cisco, Nokia), CPUs and edge inference chips (Intel), power management and analog chips (Texas Instruments).

How can computing hardware regain its "scarcity premium"?

　　The resurgence of the "Seven Knights," mainly hardware products, is just a phase rotation, or a sustainable trend?

　　Most institutions lean toward the latter answer: this is not just a simple style switch, but a structural reshaping of value distribution in the AI industry chain.

　　From the industry side, Ma Tianyi and others from the electronics team at Founder Securities believe that over the past two years, global computing power demand has shown exponential growth. As large models evolve from "perception" and "generation" to "reasoning" and "action (task execution)," the consumption of computing power has surged sharply. Against this backdrop, the architecture of computing power is shifting from purely "chip-driven" to "system collaboration-driven," and technological iteration of supporting infrastructure has become an inevitable trend.

　　Goldman Sachs research reports also point out that as enterprises accelerate infrastructure development, AI-related expenditures will continue to drive growth in equipment and construction investments in 2026. Currently, investments in AI are flowing into servers, semiconductors, storage, power infrastructure, data centers, software, and R&D.

Can the surge continue?

　　The rapid rise of the "Seven Knights" under the AI infrastructure boom has excited the market but also subtly tightened a string: will this AI boom repeat the dot-com bubble of the late 1990s?

　　In terms of investment intensity, since Q4 2022, the proportion of AI investment in the U.S. GDP has increased by 1 percentage point, leaving room to reach the 1.4% peak seen during the internet revolution; from corporate financial indicators, the market value gains of leading U.S. tech companies still align with profits, with no signs of the "market cap far exceeding profits" disconnect seen during the internet bubble. Additionally, financial metrics such as cash-to-market value ratio, ROE, and net profit margin of top tech firms are stronger than those of leading companies during the bubble period, indicating that AI investments are built on a relatively solid financial foundation.

　　It is important to note that a solid "foundation" does not mean "windless at the top." Several institutions warn that as cloud providers' AI arms race heats up, the sustainability of related capital expenditures will be a key issue to watch in the coming period.

　　Currently, the AI computing demand is mainly driven by large-scale enterprises like the "Seven Giants." Zhao Wei's team estimates that by 2026, the capital expenditure growth rate of the "Seven Giants" could exceed 60%. However, maintaining high growth into 2027 remains uncertain, as grid bottlenecks, equipment shortages, and local opposition to data center construction could become practical obstacles, potentially leading to project delays or cancellations.

　　Moreover, massive capital expenditures ultimately need revenue from application endpoints to pay for them. He Li pointed out that the ROI verification window for AI investments is approaching. If cloud providers cannot demonstrate sufficient revenue growth from AI capital expenditures in 2027-2028, the chain reaction of spending cuts could be severe. Zhao Wei's team also believes that since 2023, the profit margins and safety margins of major tech companies have narrowed beyond expectations, which could trigger market doubts about the rationality of future capital expenditures.

---Only when the speed of generating revenue in the business cycle outpaces the rate of burning cash can this AI industry expansion form a healthy cycle and truly pass through the cycle.