Applied Materials (AMAT.US), one of the world's largest semiconductor equipment manufacturers, reported its latest quarterly results and future outlook after the U.S. market closed on Thursday. The data revealed that the company, which supplies nearly the full suite of high-end semiconductor manufacturing tools, delivered quarterly results that surpassed expectations and provided an exceptionally strong guidance range. This underscores that amid the global wave of AI computing infrastructure development and the macro backdrop of a "memory chip super cycle," semiconductor equipment manufacturers are entering a period of supercharged growth. They are poised to be the largest beneficiaries of the rapid capacity expansion trends for AI chips (including AI GPUs and AI ASICs) and DRAM/NAND memory chips. Applied Materials' stock surged over 14% in after-hours trading, primarily driven by its unexpectedly robust revenue forecast, indicating that demand for AI and memory-related semiconductors is significantly accelerating purchases of high-end manufacturing equipment by leading chipmakers like TSMC.

Regarding the highly anticipated performance outlook, this largest U.S.-based supplier of semiconductor manufacturing and advanced packaging equipment projected fiscal second-quarter 2026 revenue to be approximately $7.65 billion, plus or minus about $500 million. This compares to Wall Street analysts' average revenue expectation of $7.03 billion for the quarter ending in April. Notably, as capacity expansion for 3nm and more advanced process AI chips, CoWoS/3D advanced packaging, and DRAM/NAND memory chips accelerates substantially, analysts have been consistently raising their revenue expectations for Applied Materials throughout the year. The company's management also provided a non-GAAP EPS guidance range of $2.44 to $2.84 for the second fiscal quarter (excluding certain items), far exceeding the average analyst estimate of $2.29.

Applied Materials CEO Gary Dickerson stated in a release that "the acceleration of overall industry investment in AI computing" is driving the company towards a strong growth trajectory. For the first quarter of fiscal 2026, ended January 25th, revenue was $7.01 billion, a slight decrease of 2% year-over-year. However, this decline was much smaller than the company's previous forecast and significantly stronger than the Wall Street consensus estimate of approximately $6.86 billion. Non-GAAP EPS for the first quarter was $2.38, beating the average analyst estimate of $2.21 and remaining largely flat compared to the same period last year. The company's gross margin reached 49%, up from 48% a year ago, and non-GAAP free cash flow for the quarter was a substantial $1.04 billion, representing a significant increase of 91%.

A major highlight of the report is the strong equipment demand driven by memory chip expansion. Applied Materials is rebounding strongly from a slowdown induced by a new round of U.S. government restrictions on semiconductor equipment exports to China, which has long been its largest market. However, in recent years, many of Applied Materials' high-end semiconductor manufacturing tools have been restricted from export to China. Demand for semiconductor equipment related to DRAM/NAND memory chip capacity expansion stands out as a particularly strong growth highlight in this latest quarterly report and outlook, indicating that major customers like Samsung Electronics, Micron Technology, and SK Hynix are accelerating capacity expansion to address severe market shortages. Following the strong outlook released on Thursday, the stock rose to a high of $375 in after-hours trading. Year-to-date, the stock has surged 28%, closing at $328.39 on Thursday.

Dickerson mentioned on the earnings call that exceptionally strong demand for High Bandwidth Memory (HBM)—a high-performance memory used in AI computing systems—is a key driver. "We expect the semiconductor equipment business to grow significantly, by more than 20% this calendar year," he said. HBM is a high-bandwidth, low-power memory technology specifically designed for high-performance computing and graphics processing. Utilizing 3D stacking technology, HBM interconnects multiple stacked DRAM chips via fine Through-Silicon Vias (TSVs) to achieve high-speed, high-bandwidth data transmission, and is used alongside AI GPUs like NVIDIA's GB200/GB300 and Google's TPU AI chips. The essence of HBM systems is shifting DRAM optimization from "per-chip density/cost" to "system-level interconnect optimization for GPU bandwidth/power efficiency." Higher stack layers, greater I/O density, and more aggressive interconnect pitches significantly intensify key DRAM manufacturing processes (deep hole etching, dielectric/barrier layer deposition, metal interconnection and planarization, defect/topography control). Concurrently, HBM, as a critical supply for AI computing systems, is also increasing the urgency for industry-wide capacity expansion and yield ramp-up.

The three dominant memory chip manufacturers—SK Hynix, Samsung, and Micron—are concentrating a majority of their capacity on HBM systems. These memory products require more advanced process nodes and involve significantly greater manufacturing and packaging/test complexity compared to DDR series or HDD/SSD memory chips. Consequently, the migration of capacity towards HBM by these leaders is largely contributing to supply shortages for standard memory products targeting industrial, electric vehicle, and consumer electronics applications. The CEO of U.S. memory giant Micron Technology stated on their fiscal first-quarter 2026 earnings call that the company's entire HBM capacity for 2026 is already sold out, and projected the total addressable market (TAM) for HBM to reach $100 billion by 2028 (compared to approximately $35 billion in 2025). A Bloomberg Intelligence research report indicated that Applied Materials' etching and deposition tools used for manufacturing DRAM memory chips "will expand due to extremely strong demand from AI chip customers like NVIDIA."

The earnings report also showed the company recently resolved a notable regulatory issue. Earlier this week, Applied Materials announced a plan to pay $252.5 million to settle a U.S. Department of Commerce investigation regarding improper exports to China, concluding a multi-year investigation. Undoubtedly, stricter U.S. export controls have also significantly negatively impacted the company's fundamentals. In October, Applied Materials stated that the expansion of U.S. restrictions on China would cost it approximately $600 million in revenue in fiscal 2026. The Santa Clara, California-based semiconductor equipment giant also announced plans to reduce its global workforce by 4%. Although Applied Materials' stock rose 58% last year, it still lagged behind the explosive performance of other U.S. semiconductor equipment manufacturers. For instance, Lam Research Corp.'s stock nearly doubled, and KLA Corp.'s stock rose 93% over the same period. Following Applied Materials' strong outlook on Thursday, these stocks also saw gains in after-hours trading.

The野蛮 expansion of AI computing power and memory chip demand is ushering in a super cycle for semiconductor equipment. Recent reports from several Wall Street financial giants highlight the semiconductor equipment sector as one of the biggest winners under soaring AI computing and storage demand. As the global construction of hyperscale AI data centers, led by tech giants like Microsoft, Google, and Meta, intensifies, it comprehensively drives accelerated capacity expansion for 3nm and more advanced process AI chips, CoWoS/3D advanced packaging, and DRAM/NAND memory chips by major chip manufacturers. The long-term bullish thesis for the semiconductor equipment sector is becoming increasingly robust. Following Google's major launch of the Gemini 3 AI application ecosystem in late November, this cutting-edge AI software quickly gained global popularity, causing a sudden surge in Google's AI computing demand. The Gemini 3 series products immediately generated massive AI token processing volumes, forcing Google to significantly reduce free access limits for Gemini 3 Pro and Nano Banana Pro and impose temporary restrictions even on Pro subscribers. Combined with the recent instant popularity of a series of AI tools/agentic AI collaboration platforms launched by "OpenAI rival" Anthropic, and recent South Korean trade export data showing持续强劲 demand for HBM systems and enterprise SSDs from SK Hynix and Samsung Electronics, this further validates Wall Street's assertion that the "AI boom is still in the early construction phase where computing infrastructure supply cannot meet demand."

This unprecedented wave of AI infrastructure development and the memory super cycle are pushing semiconductors into a new phase characterized by greater "material intensity, process control intensity, and the forward shift of packaging processes." On the logic side, there's the叠加 of three-dimensional structures and new materials; on the memory side, HBM stacking and interconnect upgrades; on the packaging side, CoWoS/hybrid bonding converting system performance into manufacturing complexity—these three forces collectively increase the value density of key segments like deposition/etching/CMP/advanced packaging/core metrology, and are shifting semiconductor equipment demand more distinctly from "cyclical fluctuations" to "structural mega-expansion cycles." It is particularly noteworthy that advanced packaging is accelerating its transition from the "solder bump era" to the "hybrid bonding era." Hybrid bonding, utilizing direct copper-to-copper interconnects, further shortens interconnect lengths, increases I/O density, and reduces power consumption, precisely addressing the extreme constraints on bandwidth, latency, and power consumption in AI training/inference. Applied Materials not only systematically explains the performance/power advantages of hybrid bonding compared to TSV on its website but has also launched a platform for scaled hybrid bonding and strengthened its industry position through strategic "process-equipment synergy" by investing in BESI (a leader in hybrid bonding equipment).

Global demand for AI computing infrastructure and enterprise-grade memory chips for data centers continues to show an exponential growth trend, with supply struggling to keep pace with demand intensity. This is clearly evident from the exceptionally strong recent financial data released by the "world's chip king," TSMC (TSM.US). TSMC's fourth-quarter gross margin exceeded 60% for the first time, net profit significantly beat expectations, and the company forecasts nearly 30% revenue growth for full-year 2026. Furthermore, TSMC substantially raised its 2026 capital expenditure guidance to $52-$56 billion. Both core guidance figures far exceeded market expectations. Additionally, TSMC management significantly raised its compound annual growth rate (CAGR) expectation for its AI-related chip foundry business from the "mid-40% range" to the "mid-to-high 50% range." The exceptionally strong performance and future guidance from this world's largest chip manufacturer have recently fueled a rally in chip stocks, particularly memory chips and semiconductor equipment, as TSMC's capital expenditure expansion is primarily for purchasing various high-end semiconductor equipment covering lithography, etching, thin-film deposition, advanced packaging, testing, and other chip manufacturing steps.

Within chip fabrication plants, the presence of Applied Materials (AMAT.US) is virtually ubiquitous. Unlike ASML, which remains focused on lithography, U.S.-based Applied Materials provides high-end equipment critical to almost every step of the chip manufacturing process. Its product portfolio encompasses crucial chip-making steps such as Atomic Layer Deposition (ALD), Chemical Vapor Deposition (CVD), Physical Vapor Deposition (PVD), Rapid Thermal Processing (RTP), Chemical Mechanical Polishing (CMP), wafer etching, and ion implantation. Applied Materials possesses high-precision manufacturing equipment and customized solutions for two key chiplets advanced packaging areas: wafer Hybrid Bonding and Through-Silicon Via (TSV), which are essential for TSMC's 2.5D/3D level advanced packaging steps. In its latest technical commentary, Applied Materials pointed out that the HBM manufacturing process involves approximately 19 additional materials engineering steps compared to traditional DRAM and claims its most advanced semiconductor equipment covers about 75% of these steps. The company has also significantly launched bonding systems targeting advanced packaging/memory chip stacking, positioning HBM and advanced packaging manufacturing equipment as strong medium-to-long-term growth vectors. New chip manufacturing node equipment, such as Gate-All-Around (GAA) and Backside Power Delivery (BPD), are expected to be core drivers for the company's next wave of strong growth.