Applied Materials makes unexpected AI move as demand explodes
π¬ Applied Materials (AMAT) announced a new co-innovation partnership with TSMC days before its fiscal second-quarter earnings report on May 14.
ποΈ The collaboration will take place inside Applied's $5 billion EPIC Center in Silicon Valley, representing the largest U.S. investment ever in advanced semiconductor R&D.
π€ TSMC has joined as a founding partner of the EPIC Center, leveraging its dominant position with approximately 70% market share in advanced chips in 2025.
π AMAT stock has surged 189.52% over the past year and is up 73.97% year-to-date, driving Morgan Stanley to raise its price target to $454.
π¬ CEO Gary Dickerson emphasized the long-standing trust between Applied and TSMC aimed at advancing innovation at the leading edge of semiconductor technology.
π The EPIC Center is designed to compress the timeline between early-stage research and full-scale high-volume manufacturing for AI-driven processes.
βοΈ The partnership focuses on process technologies for power and performance, new materials for 3D transistors, and advanced integration for vertically stacked architectures.
π£οΈ TSMC EVP Y.J. Mii stated that global AI challenges require industry-wide collaboration to accelerate equipment readiness for next-generation technologies.
π° In fiscal Q1 2026, Applied reported $7.01 billion in revenue, a drop of 2% year over year, but GAAP EPS jumped 75% to $2.54.
π Non-GAAP margins remained strong at 49.1%, while the company returned $702 million to shareholders via buybacks and dividends in Q1 2026.
π― For fiscal Q2 2026, Applied guided for revenue of approximately $7.65 billion and non-GAAP EPS of $2.64, building on a track record of beating estimates for four consecutive quarters.
π CFO Brice Hill noted the company has nearly doubled system manufacturing capability in preparation for sustained market growth driven by AI infrastructure demand.
π Applied Materials dominates key segments like high-bandwidth memory DRAM and advanced packaging, which are central to AI accelerator production.
π The stock traded at $447.27 on May 11 with a massive 190% gain over the past year, significantly outpacing the S&P 500's 31.13% gain.
- Applied Materials unveiled a new $5 billion EPIC Center co-innovation partnership with TSMC, the world's largest chip foundry with an estimated 70% market share in advanced chips for AI.
- Management signaled strong confidence in upcoming results after being up 73.97% year to date and seeing Morgan Stanley raise its price target to $454 from $432.
- In fiscal first quarter 2026, GAAP EPS surged 75% year over year to $2.54, while the company returned $702 million to shareholders through buybacks and dividends.
- Applied Materials has beaten earnings estimates in each of the past four quarters with an average surprise of 5.24%, according to Zacks.
- The company guided for second-quarter revenue of approximately $7.65 billion, suggesting continued strength before its May 14 earnings report.
- CFO Brice Hill noted that system manufacturing capability was nearly doubled over recent years in preparation for significant market growth driven by AI infrastructure spending.
- Applied holds leadership positions in high-bandwidth memory DRAM, advanced packaging, and leading-edge logic, all critical segments where AI spending is concentrated.
- The stock returned 190% over the past year, significantly outperforming the S&P 500's 31.13% gain, indicating sustained investor optimism.
- Revenue fell 2% year over year in the fiscal first quarter of 2026, despite strong earnings growth.
- Non-GAAP gross margin was flat year over year at $49.1%, indicating a potential lack of pricing power or cost pressures.
- The market questions whether upcoming July quarter guidance will match current momentum and beat expectations.
- The stock has appreciated nearly 200% over the past year, entering territory where investors may be taking profits rather than accumulating.
- Applied Materials built system manufacturing capability by 'nearly doubling' over several years, which now exposes them to inventory risks if AI demand softens before they can deploy that capacity.