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Applied Materials and KIOXIA Team Up on new AI Memory at the EPIC Center. Quick read summary. * Applied Materials and KIOXIA are collaborating on memory structures, chip stacking and materials engineering for AI workloads. * KIOXIA will join the EPIC Center ecosystem as an innovation partner. * The work targets higher memory density, bandwidth and energy efficiency as AI systems place greater demands on memory. Why memory is the next bottleneck. AI workloads consume large amounts of data and often operate across many processors simultaneously. High-bandwidth memory has become essential for accelerator systems because it can move data at rates that conventional memory architectures cannot match. But increasing bandwidth is only one part of the problem. More memory capacity is also needed, and adding physical components increases packaging complexity. Engineers So have to improve density without making the system too large, hot or expensive. That is where advanced stacking and materials engineering become important. Instead of treating memory chips as isolated components, designers can combine multiple dies and improve the connections between them. The role of the EPIC Center. The EPIC Center can shorten the distance between semiconductor research and manufacturing. Bringing equipment specialists and memory companies together allows new processes to be tested in an environment closer to production. For KIOXIA, the partnership provides access to materials and process expertise. For Applied Materials, working with a major memory manufacturer provides a direct way to test whether new equipment and process ideas solve real manufacturing problems. Stacking changes the package. Multi-chip stacking can increase memory density without simply expanding the footprint of the package. But stacked systems introduce problems around heat, interconnects, manufacturing yield and mechanical reliability. You Might Be Interested In The connection between memory and processor also matters. Every additional layer in the data path can introduce latency or power consumption. AI systems are particularly sensitive to those costs because accelerators may perform billions of operations while waiting for data. The Applied Materials-KIOXIA work shows how AI is pushing semiconductor innovation beyond the processor itself. Faster accelerators need faster and denser memory, and that requirement is driving new work in materials, packaging and manufacturing. The new of AI hardware will be defined by the complete system rather than by the compute chip alone. The partnership also reflects the growing importance of NAND and other memory technologies outside conventional DRAM. AI infrastructure needs both fast working memory and large, efficient storage. Improvements in density and packaging can affect how data is staged between those layers. Bringing memory development into the same environment as semiconductor equipment research can shorten the feedback loop between a process idea and a manufacturing result. That is especially valuable when new AI memory architectures have to balance performance with yield and cost. The work is also relevant to the economics of AI memory. Higher density can reduce the number of packages required for a given capacity, but advanced stacking and materials can add manufacturing complexity. Engineers So have to improve performance without allowing cost and yield to move in the wrong direction. KIOXIA's participation also broadens the EPIC ecosystem beyond the companies developing accelerator memory directly. Flash storage and advanced memory increasingly sit in the same AI data path, from persistent datasets to high-speed working memory. The result is a more integrated view of memory. AI systems need fast access close to the processor, large pools farther away and efficient movement between them. Semiconductor research is increasingly organized around that entire hierarchy. AI memory is also increasingly affected by packaging limits. As more memory is placed close to an accelerator, thermal density and manufacturing yield become harder problems. A successful design So has to improve bandwidth without creating a package that is too difficult or expensive to manufacture. The EPIC Center model aims to shorten this development loop by giving ecosystem partners access to equipment and process research earlier. That can help identify manufacturing problems before a technology is committed to a high-volume production line. For AI hardware, that speed matters because model and accelerator generations are changing quickly. A memory technology that takes too long to reach production can arrive after the workload it was designed for has already changed. The memory work is also connected to the growing importance of energy efficiency. Large AI clusters consume substantial power, and moving data can consume a significant share of that budget. Higher-density memory can reduce the physical footprint, while improved interconnects can reduce the energy cost of data movement. The challenge is to improve density without creating thermal problems. Stacked memory places more components close together, so materials and packaging become part of the thermal solution and the electrical one. That is why partnerships between memory manufacturers and equipment companies matter. A new memory structure is only useful if the equipment can manufacture it consistently and at a cost that makes the resulting product viable. Memory research is increasingly tied to the physical limits of advanced packaging. As more dies are stacked into smaller spaces, engineers have to manage heat, electrical connections and manufacturing yield at the same time. AI workloads make the problem more urgent because accelerators can consume enormous amounts of data and benefit directly from higher bandwidth. The Applied Materials and KIOXIA partnership So sits at the intersection of materials science, process equipment and system architecture. Progress in any one area is useful, but the real advantage comes when the pieces are developed together. That is why collaborative semiconductor research centers are becoming strategically important to the AI hardware supply chain. You Might Be Interested In

AMAT stock has doubled this year: analyst trims price target but sees higher 2027 sales, profit. Published: Sep 30 2026, 08:00 AM IST * FB * TW * Linkdin * Whatsapp * GNFollow Us AI-driven memory demand puts semiconductor equipment spending back in focus. * Morgan Stanley raised its 2027 revenue forecast for Applied Materials to $50.7 billion and its EPS estimate to $20.92, citing higher NAND demand and better margins. * KIOXIA will join Applied Materials' EPIC Center to collaborate on advanced memory structures, stacking, packaging and materials engineering. * AMAT stock doubled year to date, and retail traders see Micron's quarterly report, due on Wednesday, as a fresh catalyst. Applied Materials (AMAT) shares jumped 5.2% on Tuesday, making the semiconductor equipment maker the top gainer on the Nasdaq-100 and pushing the stock to its highest level since Aug. 18, after Morgan Stanley raised its expectations for the company's 2027 financials. In after-hours trading, the company announced a partnership with Japan's KIOXIA to develop next-generation memory technologies. The stock, however, dipped 0.2% in overnight trading following the announcement. Morgan Stanley ups AMAT's 2027 forecasts. Morgan Stanley on Monday cut its price target for AMAT to $563 from $642, which still signals a 25% upside, while maintaining an 'equal weight' rating. However, the research firm simultaneously raised its projections for Applied Materials' 2027 revenue and EPS, signaling stronger earnings expectations despite the lower valuation target. Morgan Stanley raised the revenue forecast to $50.7 billion and EPS estimate to $20.92, driven primarily by expectations for higher NAND demand and improved gross margins. AMAT-KIOXIA partnership. Applied Materials said KIOXIA, a major supplier of flash memory and solid-state drives, will join its EPIC Center in Silicon Valley as an innovation partner. The companies will work on advanced memory structures, multi-chip stacking, advanced packaging and materials engineering aimed at increasing memory density, bandwidth and energy efficiency for AI applications. The announcement does not represent a newly disclosed equipment purchase by KIOXIA. Instead, KIOXIA will collaborate with Applied Materials on research and development at the EPIC Center to accelerate the commercialization of new memory and packaging technologies. Applied Materials: AI memory opportunity. Applied Materials' $5 billion EPIC Center is designed to bring chipmakers, equipment companies, universities and other partners together to develop semiconductor processes and move them more quickly from research into high-volume manufacturing. The center gives chipmakers earlier access to Applied Materials' technologies and the company said in August that its EPIC Center had expanded to 11 R&D engagements. For investors, the KIOXIA tie-up reinforces the potential for AI-driven memory demand to translate into equipment spending. As memory architectures become more complex, manufacturers require additional process steps, materials and advanced packaging capabilities, potentially increasing the amount of semiconductor equipment required per wafer. AMAT stock move, retail view. These developments come as semiconductor equipment stocks have gained significantly in 2026, despite a pullback from their June peaks, driven by expectations of elevated AI-related chip spending. Applied Materials stock has doubled this year, while KLA Corp. (KLAC) is up 62.3% and Lam Research (LRCX) is up 90%. On Stocktwits, retail sentiment for AMAT dipped in recent days and was 'neutral' on Tuesday, with traders linking gains in AMAT and peers KLA Corp. and Lam Research to Micron's upcoming quarterly report. "Bullish prelude to Micron's $MU future Earnings are already here. Semi equipment names related to Micron's capex - $AMAT $KLAC $LRCX were all trending down. But recently all of them together got above all moving averages and trending up," a trader said. "Certainly a strong indication that Micron's sustained demand and earnings are going to be good." For updates and corrections, email newsroom[at]stocktwits[dot]com.< Stay updated with all the latest Business News, including market trends, Share Market News, stock updates, taxation, IPOs, banking, finance, real estate, savings, and investments. Track daily Gold Price changes, updates on DA Hike, and the latest developments on the 8th Pay Commission. Get in-depth analysis, expert opinions, and real-time updates to make informed financial decisions. Download the Asianet News Official App from the Android Play Store and iPhone App Store to stay ahead in business. 0 Comments / 0 New

Morgan Stanley cuts Applied Materials stock target to $563, raises 2027 forecasts. 2026-09-29 18:46:45 Key takeaways. * Morgan Stanley lowered Applied Materials' price target to $563 from $642 on the 30th while maintaining Overweight rating. * Morgan Stanley raised Applied Materials' 2027 revenue forecast to $50.7 billion and EPS to $20.92 due to stronger NAND demand. * Japan's Kioxia joined Applied Materials' EPIC Center partnership alongside Samsung Electronics and SK Hynix. Morgan Stanley lowered its price target for global semiconductor equipment maker Applied Materials (NAS:AMAT) from $642 to $563 while maintaining an Overweight rating, according to The Street on the 30th. The adjustment came despite the firm raising its 2027 revenue forecast to $50.7 billion and earnings per share (EPS) to $20.92, driven by increased NAND demand and improved gross margin expectations. The new target represents approximately 10% upside from Applied Materials' closing price of $512.01 on the 29th, which rose 5.19% from the previous day. Morgan Stanley raises 2027 revenue and EPS forecasts despite target cut. Morgan Stanley increased its 2027 revenue projection for Applied Materials to $50.7 billion with EPS of $20.92, citing stronger NAND demand and improving gross margins. The firm stated, "The market is positive on Applied Materials, and we agree," adding that it prefers stocks where expectations are less reflected in multiples. The revised target of $563 maintains the Overweight rating despite being lowered from the previous $642 target. Applied Materials stock performance shows strong gains. Applied Materials stock has risen 89% this year and 139% over the past year. The stock closed at $512.01 on the 29th, up 5.19% from the previous day. Morgan Stanley's new $563 target represents approximately 10% upside from this closing price. Kioxia joins Applied Materials EPIC Center partnership. Applied Materials announced on this day that Japan's Kioxia has joined as an innovation partner at its EPIC Center located in Silicon Valley. The EPIC Center serves as a facility for semiconductor process technology and manufacturing equipment R&D collaboration. Samsung Electronics and SK Hynix also participate in the EPIC Center. Faq. What did Morgan Stanley do with Applied Materials stock target on the 30th? Morgan Stanley lowered Applied Materials' price target from $642 to $563 while maintaining an Overweight rating, according to The Street. The firm simultaneously raised its 2027 revenue forecast to $50.7 billion and EPS to $20.92, citing increased NAND demand and improved gross margin expectations. Why did Morgan Stanley cut the target despite positive outlook? Morgan Stanley stated it prefers stocks where expectations are less reflected in multiples, despite agreeing with the market's positive assessment of Applied Materials. The new $563 target still represents approximately 10% upside from the stock's $512.01 closing price on the 29th. Disclaimer: The information on this page may come from third-party sources and is for reference only. It does not represent the views or opinions of Gate and does not constitute any financial, investment, or legal advice. Virtual asset trading involves high risk. Please do not rely solely on the information on this page when making decisions. For details, see the Disclaimer.