According to the Zhitong Finance APP, during a recent earnings conference call, semiconductor equipment giant ASML (ASML.US) indicated that management expects both 2025 and 2026 to be years of performance growth, and anticipates that dynamic demand in the end market will shift the chip product mix towards high-end AI chips and data center storage chips. This semiconductor equipment giant, regarded as the "pinnacle of human technology," emphasized that the demand for AI computing power remains strong under the pressure of tariffs, and as the focus of AI computing power shifts towards the seemingly endless demand in the AI inference field, this has already been confirmed by high-end lithography machine customers, who have expressed the need for continued large-scale investment in the AI technology sector.Taiwan Semiconductor (TSM.US), known as the "king of chip foundries," also reported a surge in AI computing power demand in its earnings released on Thursday, with net profit soaring by 60%. More importantly, under the heavy pressure of tariffs imposed globally by Trump, Taiwan Semiconductor reaffirmed its strong performance growth data. Taiwan Semiconductor maintains its revenue growth forecast for 2025, expecting this year's growth rate to still reach around 25%, fully consistent with the target set in January, with revenue related to artificial intelligence (AI) expected to double.Regarding tariff-related issues that are the focus of global investors, Taiwan Semiconductor stated that it has not observed any changes in customer behavior due to U.S. tariffs, and its optimistic outlook contrasts sharply with the uncertainty in the global market. Notably, Taiwan Semiconductor plans to double its CoWoS advanced packaging capacity, primarily for NVIDIA's AI GPU capacity, which also indicates the company's strong confidence that the demand for AI chips will remain robust until early 2026.In the earnings conference call, Taiwan Semiconductor's management still expects a compound annual growth rate target of about 20% for revenue over the next five years (2024-2029), with AI-related revenue expected to grow by around 45%, fully consistent with the strong expectations given in the last earnings meeting, suggesting that Taiwan Semiconductor has not seen any degree of demand cooling due to Trump's aggressive global tariff policy. Regarding the expectations for the second quarter, Taiwan Semiconductor's management expects Q2 revenue to be in the range of $28.4 billion to $29.2 billion, implying a quarter-on-quarter growth of over 13% and a year-on-year growth of over 36%, far exceeding the market expectation of $27.16 billion; it maintains its capital expenditure for 2025 at $38 billion to $42 billion.In late March, U.S. largest computer storage chip manufacturer Micron Technology (MU.US) reported that thanks to the AI infrastructure frenzy, where large global enterprises and various government departments are investing heavily in AI, the demand for storage chips closely related to AI training/inference systems remains extremely strong, driving a significant increase in Micron's data center business revenue, including HBM storage systems and enterprise-level SSDsMicron's management stated during the earnings conference call that they are seeing an incredibly strong demand for data center AI infrastructure components used to develop iterations and operate high-efficiency artificial intelligence application software, including so-called "AI agents." Coupled with the latest performance announcements from Taiwan Semiconductor and ASML, as well as summaries from their management earnings calls, this significantly reinforces the extremely optimistic outlook for the explosive growth of AI computing power demand. Currently, even the aggressive tariff policies of the Trump administration aimed at the global market have not suppressed the continuously surging demand for AI computing power centered around AI chips.With DeepSeek completely igniting an "efficiency revolution" in AI training and inference, focusing future AI large model development on "low cost" and "high performance," the super wave of AI large models integrating into various industries globally is expected to catalyze exponential growth in cloud AI inference computing power demand. AI application software (especially generative AI software and AI agents) is accelerating its penetration into various industries worldwide, fundamentally revolutionizing the efficiency of various business scenarios and significantly increasing sales. The demand for AI computing infrastructure, such as AI GPUs and AI ASICs, may exhibit exponential growth in the future rather than the previously anticipated "DeepSeek shockwave" leading to a cliff-like decline in AI computing power demand.As Jensen Huang, CEO of NVIDIA, stated during NVIDIA's earnings call in February, the demand for AI chips continues to grow strongly. "DeepSeek-R1 has ignited global enthusiasm, and the company is excited about the potential demand brought by AI inference. This is an outstanding innovation, but more importantly, it has opened up a world-class inference AI model. Models like OpenAI, Grok-3, and DeepSeek-R1 are inference models that scale with application inference time. Inference models can consume over 100 times the computing power."According to the latest forecast from the World Semiconductor Trade Statistics (WSTS), the global semiconductor market size is expected to continue growing in 2025 based on 2024, indicating that the global semiconductor market is likely to grow by about 11.2% on top of the already strong recovery trend in 2024, with the global market size expected to reach approximately $697 billion.WSTS predicts that the growth of the semiconductor market size in 2025 will be primarily driven by strong enterprise-level storage chip categories and artificial intelligence logic chip categories fueled by robust AI training/inference computing power demand. It is expected that the overall market size of logic chip categories, including CPU, GPU, and ASIC chips, will grow by about 17% year-on-year in 2025. The market size of storage chip categories covering HBM, enterprise-level SSDs, etc., is expected to grow by over 13% year-on-year on top of a significant 81% growth in 2023; at the same time, WSTS also expects the growth rates of all other segmented chip markets, including discrete devices, optoelectronics, sensors, MCUs, and analog chips, to reach single-digit increasesAs Global Stock Markets Experience Severe Volatility, the "Alpha" Attributes of the AI Computing Sector Stand OutMorgan Stanley, the Wall Street financial giant (hereinafter referred to as "Morgans"), recently released a research report indicating that AI/ML (Artificial Intelligence/Machine Learning) expenditures are prioritized in the IT budgets of technology companies in the United States, with demand for security defense software, driven by the AI wave, following closely behind.The latest survey and research results released by Morgans, which exceed 10,000 words, show a clear divergence in the IT budget expectations of U.S. CIOs, primarily influenced by macroeconomic fluctuations. Although CIOs have lowered their expectations for short-term IT budget growth, their confidence in core long-term growth drivers (such as AI/Machine Learning) and mid-term IT spending remains stable, with expectations for significant expansion in AI spending.As investors further digest and price in Trump's aggressive tariff policies aimed at the global market, the panic sentiment in global stock markets has eased, especially as technology stocks, which suffered the most severe sell-off in this round of global market declines, experienced a brief rebound. Technology stocks have been the core driving force behind the long-term bull market in global stock markets in recent years, leading investors to anticipate a resurgence of technology stocks, which have historically guided the market, to rally and lead a strong rebound in global stock markets after enduring a new round of sell-offs.A tweet released last Wednesday, suggesting a shift towards a more rational tariff stance by the Trump administration, significantly drove global stock markets, including U.S. stocks, from the ICU to a KTV celebration. Trump stated that he had authorized a 90-day "reciprocal tariff suspension" measure for most countries, during which tariffs for these countries would be significantly reduced to 10%.The "tariff tsunami" largely instigated by Trump caused the evaporation of hundreds of billions of dollars in market value across global stock markets, pushing Wall Street traders and global financial market investors to the brink of despair and collapse, urging them to "sell everything you can sell." However, after Trump announced the latest news of the suspension of "reciprocal tariffs" on his personally founded social platform Truth Social last week, last Wednesday was marked as a "miracle day" for U.S. stocks, leading to a super rebound that propelled global stock markets in an epic upward trend, after which global stock markets had previously seen over $10 trillion in market value evaporate.For the "AI computing industry chain," which has consistently ranked at the top of global stock market investment enthusiasm since 2023, Morgans' research report indicates that the bullish investment logic for artificial intelligence is gradually recovering as the financial market refocuses on the strong demand expectations for AI infrastructure such as AI chips. After all, compared to the non-AI sectors in the semiconductor field, the demand expectations for AI GPUs, AI ASICs, HBM, Ethernet switch chips, and core power equipment among the "leaders in AI computing" are significantly stronger, and they are expected to show the strongest leading trend during short-term rebound markets such as "tactical rebounds."**Morgan Stanley's latest research shows that technology stocks most closely associated with AI/ML, especially the long-standing leaders in the AI computing power supply chain—such as chip giants Nvidia, Broadcom, Micron, and Taiwan Semiconductor—are expected to demonstrate "alpha excess returns" far superior to the S&P 500 index and the Nasdaq 100 index, known as the "barometer of tech stocks," during the tactical rebound of U.S. stocks. The so-called "alpha" is defined as the actual investment returns far exceeding "beta returns"—which refer to the synchronous investment return data that far exceeds those tracking benchmark stock indices. The synchronous returns achieved by tracking benchmark indices are also known as "beta returns."Statistics show that U.S. stocks experienced significant turbulence in April, but the alpha characteristics of AI chip giants have fully emerged, with the AI computing power supply chain beginning to show a leading trend. For example, Broadcom, one of the leaders in AI chips, saw a rise of over 2% in April, while the S&P 500 index fell by as much as 6%. Nvidia's high-speed copper cable supplier Amphenol (APH.US) also significantly outperformed the S&P 500 index. In Asia, leaders in the AI computing power supply chain such as SK Hynix, Tokyo Electron, and SMIC have all significantly outperformed the market, while in Europe, ASM International and BE Semiconductor from the Netherlands have also greatly outperformed the European stock market.The investment research platform Seeking Alpha's latest compilation of the top ten semiconductor stocks in the U.S. based on quantitative indicators shows that AI chip giants are likely to gain more favor from institutional and retail investors under the "tariff storm" of the Trump administration. Data compiled by Seeking Alpha indicates that these stocks have a market capitalization of at least $10 billion and are ranked according to its proprietary quantitative system. As investor attention to the semiconductor industry has recently increased, this list provides a data-driven perspective to help investors understand which companies may be best positioned amid increasingly severe macroeconomic and geopolitical challenges.For reference, the Seeking Alpha quantitative system is driven by SA's unique "Quant System," which rates stocks based on overall value, growth potential, profitability, earnings per share revision trends, and price momentum indicators. The rankings show that the top two are the two major leaders in AI chips, with AI ASIC chip leader Broadcom (AVGO.US) ranking first and AI GPU leader Nvidia (NVDA.US) ranking second. The following image shows the top ten U.S. semiconductor stocks.Morgan Stanley and other major Wall Street firms continue to focus on repairing AI investment logicOn the eve of the earnings season, Wall Street's well-known investment firm Oppenheimer reiterated its preference for the "three giants of AI chips," namely NVIDIA (NVDA.US), Broadcom (AVGO.US), and Marvell Technology (MRVL.US), as top recommendations in the semiconductor sector. The Oppenheimer analyst team wrote in a report to clients: “In the chaotic macro environment and tariff backdrop, we believe that AI chips represent the strongest and safest growth direction.”A recent research report from KeyBanc Capital Markets shows that the global semiconductor industry is exhibiting a "tale of two cities" pattern—strong demand for AI chips but continued sluggish demand for other types of chips. KeyBanc analysts stated, “The strongest demand theme for AI chips is still fully dominated by NVIDIA, which holds an 80%-90% market share in the AI chip market, while other AI chip participants generally have not escaped negative catalysts.” Analysts particularly pointed out that the mass production progress of the Blackwell architecture AI GPU is going smoothly, and the demand for CoWoS advanced packaging remains stable. “Demand for AI chips continues to surge, and we also see multiple cross-layer impacts in the field of NVIDIA AI GPUs and ASICs, which are dedicated AI chips.” KeyBanc stated.International banking giant UBS released a research report stating that, although it is difficult to assert that semiconductor giants can completely avoid the demand destruction related to Trump's aggressive tariff policies, UBS firmly believes that artificial intelligence (AI) spending will remain resilient. The overall weak demand environment may force companies to accelerate the adoption of generative AI technology to reduce operating costs, thus UBS will focus more on AI computing power-driven stock targets, such as NVIDIA and Broadcom.Morgan Stanley's research report shows that Dell Technologies (DELL.US) has performed relatively well among enterprise hardware suppliers, with net spending intentions reaching +35%, up 1 percentage point from 3Q24, setting a new high level in Morgan Stanley's survey report over the past eight years, reflecting that major U.S. tech companies still have very strong core hardware demand in the AI infrastructure sector. Morgan Stanley's survey data indicates that as much as 55% of CIOs who are evaluating or planning to evaluate AI technology show a tendency to allocate to Dell's AI infrastructure solutions, slightly up from 54% in 3Q24. This survey result also means that the demand for high-performance AI servers equipped with AI GPUs and AI ASICs remains very strong.In terms of corporate AI computing power spending, American tech giants are also joining Wall Street's ranks—extremely optimistic about the expansion of AI computing resource demand. For example, Sundar Pichai, CEO of Google's parent company Alphabet (GOOGL.US), reiterated the tech giant's recent commitment to invest approximately $75 billion in building large-scale AI infrastructure for AI data centers.**Amazon (AMZN.US) CEO Andy Jassy made a rare high-profile defense of the company's massive investments in artificial intelligence in his annual open letter to shareholders last week. The leader of the American e-commerce giant stated, "When every customer experience is going to be reshaped by AI, deeply investing in artificial intelligence is not a choice but a survival imperative." Amazon's management still expects capital expenditures to reach $100 billion this year, with most of it allocated to AI-related infrastructure projects.Deutsche Bank, UBS, and Piper Sandler have slightly lowered their target price for NVIDIA in their latest research reports, but still maintain a target price of at least $135 within the next 12 months, along with the most optimistic rating equivalent to "buy." The latest ratings and target prices compiled by TIPRANKS show that Wall Street's consensus rating for NVIDIA stock is "strong buy," with no "sell" ratings; the average target price within 12 months is as high as $170, indicating a potential upside of up to 68%; the highest target price reaches $200, while the most pessimistic target price is $120—still significantly above the current stock price