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06-16

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no gambling","avatar":"https://community-static.tradeup.com/news/36fa51bb4b75c0adc6108bf97e8a90fe","crmLevel":11,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4204818795581912","idStr":"4204818795581912"},"themes":[],"title":"","htmlText":"Good&nbsp;","listText":"Good&nbsp;","text":"Good","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/575869390493288","repostId":"2643373567","repostType":2,"repost":{"id":"2643373567","kind":"highlight","weMediaInfo":{"introduction":"追踪全球财经热点，精选影响您财富的资讯，投资理财必备神器！","home_visible":1,"media_name":"华尔街见闻","id":"1084101182","head_image":"https://static.tigerbbs.com/66809d1f5c2e43e2bdf15820c6d6897e"},"pubTimestamp":1781599906,"share":"https://ttm.financial/m/news/2643373567?lang=en_US&edition=fundamental","pubTime":"2026-06-16 16:51","market":"sg","language":"zh","title":"Citrini: AMD and Apple are both betting on flash memory to replace DRAM, and memory costs may fall 55 times","url":"https://stock-news.laohu8.com/highlight/detail?id=2643373567","media":"华尔街见闻","summary":"面对DRAM暴涨，AI存储向低成本闪存转移。AMD收购MEXT将AI驱动闪存技术引入数据中心，苹果推进端侧闪存方案。巨头看重闪存成本仅为DRAM的1/55，正重构AI存储架构。","content":"<p><html><head></head><body><p style=\"text-align: left;\">The reliance on expensive DRAM for AI inference is loosening.<a href=\"https://laohu8.com/S/AMD\">AMD</a>Announced the acquisition of memory optimization company MEXT to bring AI-driven flash memory optimization technology to data centers. This marks that AI storage architecture is undergoing a structural migration, and the core driver is only one number:<strong>Flash costs only 1/55 of DRAM.</strong></p><p><p style=\"text-align: left;\">On Monday, AMD announced the completion of its acquisition of MEXT for an undisclosed amount. AI-driven predictive memory technology developed by MEXT aims to make flash memory behave closer to DRAM, expanding the available memory capacity while maintaining performance and efficiency. AMD said the acquisition will expand its AI portfolio to help data center customers improve performance, reduce total cost of ownership and accelerate workload deployment. \"The demand for memory is growing in every category of enterprise computing,\" AMD said in a statement.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/a86b38617b68e608382e6d8db9bf1389\" data-align=\"center\" tg-width=\"1024\" tg-height=\"755\"/><span></span></p><p><p style=\"text-align: left;\">The news of the acquisition spurred AMD shares to rise 7.7% to $550.75 on Monday, as the market capitalization approached the $900 billion mark, and the overall S&P 500 index rose 1.8% on the day. AMD's cumulative gain this year has reached 323%. Citi upgraded AMD to Buy from Neutral last Friday and raised its price target to $575 from $460.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/fe5a732905489dfc96d3c249e9bea543\" data-align=\"center\" tg-width=\"882\" tg-height=\"984\"/><span></span></p><p><p style=\"text-align: left;\">It is worth noting that,<a href=\"https://laohu8.com/S/AAPL\">Apple</a>The \"LLM in a Flash\" end-side scheme began as early as 2024. Behind this layout is the intensifying DRAM supply crisis. According to TrendForce data, high bandwidth memory (HBM) already accounts for about a quarter of all DRAM wafer production capacity, and DRAM contract prices skyrocketed by about 90% quarter-on-quarter in the first quarter of 2026. Citrini Research pointed out that,<strong>The demand for AI storage is so large that it needs to be undertaken by multi-layer architectures. Flash memory does not replace HBM, but undertakes the overflow demand in the capacity dimension</strong>— — This architectural restructuring is repricing the entire AI storage industry chain.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/7db9e832d1e323bc33ae1b899213dd97\" data-align=\"center\" tg-width=\"1024\" tg-height=\"825\"/><span></span></p><p><h2 style=\"text-align: left;\">Memory tax crisis: bottlenecks spread from AI to the whole economy</h2><p style=\"text-align: left;\">According to<a href=\"https://laohu8.com/S/MS\">Morgan Stanley</a>Analyst Shawn Kim's team judged earlier this month,<strong>Soaring memory prices and supply scarcity are evolving into full-blown risks to the digital economy,</strong>\"From bottlenecks in AI infrastructure, it spreads to hardware margins, device affordability, cloud costs, inflation and even policy.\" This pressure has been backed up by concrete cases: Xbox CEO Asha Sharma said last week that memory costs have risen about fivefold over the past two years, preventing the company from producing the number of gaming consoles consumers need.</p><p><p style=\"text-align: left;\">HBM's continued encroachment into DRAM capacity is a central driver of this crisis. According to TrendForce<a href=\"https://laohu8.com/S/SMSN.UK\">Samsung</a>SK Hynix,<a href=\"https://laohu8.com/S/MU\">Micron</a>According to the disclosure data of manufacturers, HBM's proportion in DRAM wafer production capacity has climbed from 2% in 2020 to 25% estimated in 2026. Very large-scale cloud vendors pre-purchase future wafer output with multi-year contracts, further compressing the available production capacity of standard chips for mobile phones and PCs.</p><p><p style=\"text-align: left;\">The construction of new DRAM capacity also faces structural constraints. Production expansion relies on EUV lithography to print finer linewidths, with each EUV device selling for about $200 million, and investment in a new fab is easy<a href=\"https://laohu8.com/S/SBAY\">tens of billions</a>US dollars, and the construction period will take years in smooth circumstances. This supply rigidity is the fundamental reason for the sustainability of this round of shortage.</p><p><h2 style=\"text-align: left;\">55x Cost Difference: The Economic Logic of Flash Replacement</h2><p style=\"text-align: left;\">According to Citrini Research,<strong>Flash costs about 1/55 of DRAM per bit — about $0.05 per GB for QLC NAND, $2.75 for DDR5 DRAM, and up to $15 for HBM3E.</strong>The available space for this spread lies in the largest single memory consumption in AI inference-the KV cache (which records the context of all previous tags in each generation step of the model, which can grow to hundreds of GB in long conversations) -which requires read speed far less than the decoding path of the model weight. For this kind of sequential data reading, the speed advantage of DRAM narrows significantly, while the capacity advantage of flash memory is fully reflected.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/8f9b061541f243d013842840b2a9af30\" data-align=\"center\" tg-width=\"1024\" tg-height=\"671\"/><span></span></p><p><p style=\"text-align: left;\">The expansion path of flash memory is also essentially different from that of DRAM. Flash increases capacity by stacking more cell layers vertically, relying on deposition and etching processes already available in existing plants, eliminating the need for new lithography nodes and taking up no EUV resources. Flash controllers are produced based on mature 6/7 nanometer processes, far from the bottleneck nodes that are restricting advanced processes.</p><p><p style=\"text-align: left;\">The previously published paper \"LLM in a Flash\" by Apple researchers provides methodological support: by storing the parameters of large language models in the device Flash memory and retrieving them to DRAM on demand, the model exceeding the upper limit of DRAM capacity can be run on the device with limited DRAM capacity, and the inference speed is 4 to 5 times and 20 to 25 times faster than the naive loading mode on the CPU and GPU respectively.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/1b87a29aa7ba0ff023c247b4f54e9951\" data-align=\"center\" tg-width=\"1024\" tg-height=\"630\"/><span></span></p><p><h2 style=\"text-align: left;\">Two paths: synchronous evolution of data center and end-side</h2><p style=\"text-align: left;\">AMD's acquisition focuses on data center scenarios. By integrating MEXT technology into AMD's data center portfolio, AMD seeks to help enterprise customers increase resource efficiency and reduce costs in AI workload deployments. Morgan Stanley's Shawn Kim team believes that despite the persistent memory shortage, AMD still has structural advantages in the competitive landscape of the cloud market-\"the demand for CPUs driven by agent AI is structurally conducive to the expansion of AMD's cloud market share.\" Citi's optimistic prediction for AMD is more based on its GPU sales and<a href=\"https://laohu8.com/S/NVDA\">NVIDIA</a>Positive competitive situation.</p><p><p style=\"text-align: left;\">The apple's path is on the side of the end. The \"LLM in a Flash\" scheme partly shifts the dependence of model reasoning on expensive cloud memory to the local Flash memory of the device, which reduces the cost of cloud computing and provides feasible memory architecture support for end-side AI applications.</p><p><p style=\"text-align: left;\">According to Citrini Research, the two major paths together point to the same conclusion:<strong>The memory level of AI reasoning is being reconstructed, and low-frequency KV cache, model weight and end-side data will gradually sink from high-priced HBM/DRAM to NAND Flash/SSD layer, forming a multi-level storage architecture.</strong></p><p><p style=\"text-align: left;\">This structural transformation is forming a multi-level transmission effect along the industrial chain. According to Citrini Research, the most direct beneficiary layer is the original NAND factory. High-capacity NAND, enterprise SSD and QLC NAND are the purest directions, including SanDisk,<a href=\"https://laohu8.com/S/WDC\">Western Digital</a>Micron and Kioxia.</p><p><p style=\"text-align: left;\">The SSD controller layer is considered to be the most persistent-the core of bringing flash really close to the memory experience lies in the controller, firmware, and NVMe architecture optimization, involving<a href=\"https://laohu8.com/S/SIMO\">Silicon Motion</a>Marvell, et al. The CXL/PCIe high-speed interconnect layer also benefits.</p><p></body></html></p>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Citrini: AMD and Apple are both betting on flash memory to replace DRAM, and memory costs may fall 55 times</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 12.5px; color: #7E829C; margin: 0;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nCitrini: AMD and Apple are both betting on flash memory to replace DRAM, and memory costs may fall 55 times\n</h2>\n<h4 class=\"meta\">\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1084101182\">\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/66809d1f5c2e43e2bdf15820c6d6897e);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">华尔街见闻 </p>\n<p class=\"h-time smaller\">2026-06-16 16:51</p>\n</div>\n</a>\n</h4>\n</header>\n<article>\n<p><html><head></head><body><p style=\"text-align: left;\">The reliance on expensive DRAM for AI inference is loosening.<a href=\"https://laohu8.com/S/AMD\">AMD</a>Announced the acquisition of memory optimization company MEXT to bring AI-driven flash memory optimization technology to data centers. This marks that AI storage architecture is undergoing a structural migration, and the core driver is only one number:<strong>Flash costs only 1/55 of DRAM.</strong></p><p><p style=\"text-align: left;\">On Monday, AMD announced the completion of its acquisition of MEXT for an undisclosed amount. AI-driven predictive memory technology developed by MEXT aims to make flash memory behave closer to DRAM, expanding the available memory capacity while maintaining performance and efficiency. AMD said the acquisition will expand its AI portfolio to help data center customers improve performance, reduce total cost of ownership and accelerate workload deployment. \"The demand for memory is growing in every category of enterprise computing,\" AMD said in a statement.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/a86b38617b68e608382e6d8db9bf1389\" data-align=\"center\" tg-width=\"1024\" tg-height=\"755\"/><span></span></p><p><p style=\"text-align: left;\">The news of the acquisition spurred AMD shares to rise 7.7% to $550.75 on Monday, as the market capitalization approached the $900 billion mark, and the overall S&P 500 index rose 1.8% on the day. AMD's cumulative gain this year has reached 323%. Citi upgraded AMD to Buy from Neutral last Friday and raised its price target to $575 from $460.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/fe5a732905489dfc96d3c249e9bea543\" data-align=\"center\" tg-width=\"882\" tg-height=\"984\"/><span></span></p><p><p style=\"text-align: left;\">It is worth noting that,<a href=\"https://laohu8.com/S/AAPL\">Apple</a>The \"LLM in a Flash\" end-side scheme began as early as 2024. Behind this layout is the intensifying DRAM supply crisis. According to TrendForce data, high bandwidth memory (HBM) already accounts for about a quarter of all DRAM wafer production capacity, and DRAM contract prices skyrocketed by about 90% quarter-on-quarter in the first quarter of 2026. Citrini Research pointed out that,<strong>The demand for AI storage is so large that it needs to be undertaken by multi-layer architectures. Flash memory does not replace HBM, but undertakes the overflow demand in the capacity dimension</strong>— — This architectural restructuring is repricing the entire AI storage industry chain.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/7db9e832d1e323bc33ae1b899213dd97\" data-align=\"center\" tg-width=\"1024\" tg-height=\"825\"/><span></span></p><p><h2 style=\"text-align: left;\">Memory tax crisis: bottlenecks spread from AI to the whole economy</h2><p style=\"text-align: left;\">According to<a href=\"https://laohu8.com/S/MS\">Morgan Stanley</a>Analyst Shawn Kim's team judged earlier this month,<strong>Soaring memory prices and supply scarcity are evolving into full-blown risks to the digital economy,</strong>\"From bottlenecks in AI infrastructure, it spreads to hardware margins, device affordability, cloud costs, inflation and even policy.\" This pressure has been backed up by concrete cases: Xbox CEO Asha Sharma said last week that memory costs have risen about fivefold over the past two years, preventing the company from producing the number of gaming consoles consumers need.</p><p><p style=\"text-align: left;\">HBM's continued encroachment into DRAM capacity is a central driver of this crisis. According to TrendForce<a href=\"https://laohu8.com/S/SMSN.UK\">Samsung</a>SK Hynix,<a href=\"https://laohu8.com/S/MU\">Micron</a>According to the disclosure data of manufacturers, HBM's proportion in DRAM wafer production capacity has climbed from 2% in 2020 to 25% estimated in 2026. Very large-scale cloud vendors pre-purchase future wafer output with multi-year contracts, further compressing the available production capacity of standard chips for mobile phones and PCs.</p><p><p style=\"text-align: left;\">The construction of new DRAM capacity also faces structural constraints. Production expansion relies on EUV lithography to print finer linewidths, with each EUV device selling for about $200 million, and investment in a new fab is easy<a href=\"https://laohu8.com/S/SBAY\">tens of billions</a>US dollars, and the construction period will take years in smooth circumstances. This supply rigidity is the fundamental reason for the sustainability of this round of shortage.</p><p><h2 style=\"text-align: left;\">55x Cost Difference: The Economic Logic of Flash Replacement</h2><p style=\"text-align: left;\">According to Citrini Research,<strong>Flash costs about 1/55 of DRAM per bit — about $0.05 per GB for QLC NAND, $2.75 for DDR5 DRAM, and up to $15 for HBM3E.</strong>The available space for this spread lies in the largest single memory consumption in AI inference-the KV cache (which records the context of all previous tags in each generation step of the model, which can grow to hundreds of GB in long conversations) -which requires read speed far less than the decoding path of the model weight. For this kind of sequential data reading, the speed advantage of DRAM narrows significantly, while the capacity advantage of flash memory is fully reflected.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/8f9b061541f243d013842840b2a9af30\" data-align=\"center\" tg-width=\"1024\" tg-height=\"671\"/><span></span></p><p><p style=\"text-align: left;\">The expansion path of flash memory is also essentially different from that of DRAM. Flash increases capacity by stacking more cell layers vertically, relying on deposition and etching processes already available in existing plants, eliminating the need for new lithography nodes and taking up no EUV resources. Flash controllers are produced based on mature 6/7 nanometer processes, far from the bottleneck nodes that are restricting advanced processes.</p><p><p style=\"text-align: left;\">The previously published paper \"LLM in a Flash\" by Apple researchers provides methodological support: by storing the parameters of large language models in the device Flash memory and retrieving them to DRAM on demand, the model exceeding the upper limit of DRAM capacity can be run on the device with limited DRAM capacity, and the inference speed is 4 to 5 times and 20 to 25 times faster than the naive loading mode on the CPU and GPU respectively.</p><p><p class=\"t-img-caption\"><img src=\"https://community-static.tradeup.com/news/1b87a29aa7ba0ff023c247b4f54e9951\" data-align=\"center\" tg-width=\"1024\" tg-height=\"630\"/><span></span></p><p><h2 style=\"text-align: left;\">Two paths: synchronous evolution of data center and end-side</h2><p style=\"text-align: left;\">AMD's acquisition focuses on data center scenarios. By integrating MEXT technology into AMD's data center portfolio, AMD seeks to help enterprise customers increase resource efficiency and reduce costs in AI workload deployments. Morgan Stanley's Shawn Kim team believes that despite the persistent memory shortage, AMD still has structural advantages in the competitive landscape of the cloud market-\"the demand for CPUs driven by agent AI is structurally conducive to the expansion of AMD's cloud market share.\" Citi's optimistic prediction for AMD is more based on its GPU sales and<a href=\"https://laohu8.com/S/NVDA\">NVIDIA</a>Positive competitive situation.</p><p><p style=\"text-align: left;\">The apple's path is on the side of the end. The \"LLM in a Flash\" scheme partly shifts the dependence of model reasoning on expensive cloud memory to the local Flash memory of the device, which reduces the cost of cloud computing and provides feasible memory architecture support for end-side AI applications.</p><p><p style=\"text-align: left;\">According to Citrini Research, the two major paths together point to the same conclusion:<strong>The memory level of AI reasoning is being reconstructed, and low-frequency KV cache, model weight and end-side data will gradually sink from high-priced HBM/DRAM to NAND Flash/SSD layer, forming a multi-level storage architecture.</strong></p><p><p style=\"text-align: left;\">This structural transformation is forming a multi-level transmission effect along the industrial chain. According to Citrini Research, the most direct beneficiary layer is the original NAND factory. High-capacity NAND, enterprise SSD and QLC NAND are the purest directions, including SanDisk,<a href=\"https://laohu8.com/S/WDC\">Western Digital</a>Micron and Kioxia.</p><p><p style=\"text-align: left;\">The SSD controller layer is considered to be the most persistent-the core of bringing flash really close to the memory experience lies in the controller, firmware, and NVMe architecture optimization, involving<a href=\"https://laohu8.com/S/SIMO\">Silicon Motion</a>Marvell, et al. The CXL/PCIe high-speed interconnect layer also benefits.</p><p></body></html></p>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/a86b38617b68e608382e6d8db9bf1389","relate_stocks":{"LU2106854487.HKD":"ALLIANZ THEMATICA \"AMG\" (HKD) INC","LU0069063385.USD":"SUSTAINABLE GLOBAL THEMATIC PORTFOLIO \"A\" (USD) ACC","LU2065169927.USD":"M&G (LUX) GLOBAL MAXIMA \"A\" (USD) ACC","LU1629891620.HKD":"ALLIANZ INCOME AND GROWTH \"AMG2\" (H2-HKD) INC","SG9999018857.SGD":"United Global Quality Growth Fd Cl Acc SGD-H","LU1935042991.SGD":"MANULIFE GF GLOBAL MULTI-ASSET DIVERSIFIED INCOME  \"AA\" (SGDHDG) INC","LU1778281490.HKD":"HSBC GIF GLOBAL LOWER CARBON EQUITY \"AD\" (HKD) INC","IE000W1ABFV2.USD":"PIMCO BALANCED INCOME AND GROWTH \"R\" (USD) INC","IE00BZ1G4Q59.USD":"LEGG MASON CLEARBRIDGE US EQUITY SUSTAINABILITY LEADER \"A\"(USD) INC (A)","LU0203202063.USD":"AB SICAV I - ALL MARKET INCOME PORTFOLIO \"A2X\" (USD) ACC","IE0009356076.USD":"JANUS HENDERSON 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(irc)","LU0143551892.USD":"T ROWE PRICE GLOBAL FOCUSED GROWTH EQUITY \"A\" (USD) ACC","LU2462591277.SGD":"TRP GLOBAL FOCUSED GROWTH EQUITY \"AN\" (SGDHDG) ACC","IE00BMPRXR70.SGD":"Neuberger Berman 5G Connectivity A Acc SGD-H","LU1084165304.USD":"FIDELITY WORLD \"A\" (USD) ACC","LU2954938101.SGD":"T ROWE PRICE GLOBAL FOCUSED GROWTH EQUITY \"A8P\" (SGD) INC","SG9999014898.SGD":"United Global Quality Growth Fund Dis SGD","LU2487616109.SGD":"JPM AMERICA EQUITY \"A\" (SGD) ACC","LU0210528500.USD":"JPM AMERICA EQUITY \"A\" ACC","LU2999663052.SGD":"T ROWE PRICE GLOBAL FOCUSED GROWTH EQUITY \"A4P\" (SGD) INC","LU0912757837.SGD":"JPMorgan Investment Funds - Global Income A (mth) SGD-H"},"source_url":"https://wallstreetcn.com/articles/3774784","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2643373567","content_text":"AI推理对昂贵DRAM的依赖正在松动。AMD宣布收购内存优化公司MEXT，将AI驱动的闪存优化技术引入数据中心。这标志着AI存储架构正在经历一场结构性迁移，而核心驱动力只有一个数字：闪存成本仅为DRAM的1/55。周一，AMD宣布以未披露金额完成对MEXT的收购。MEXT开发的AI驱动预测内存技术，旨在让闪存的行为更接近DRAM，在维持性能与效率的同时扩展可用内存容量。AMD表示，此次收购将扩充其AI产品组合，帮助数据中心客户提升性能、降低总拥有成本并加速工作负载部署。\"对内存的需求正在企业计算的每个品类中增长，\"AMD在声明中称。收购消息刺激AMD股价周一上涨7.7%至550.75美元，市值逼近9000亿美元关口，当日S&P 500指数整体上涨1.8%。AMD今年以来累计涨幅已达323%。花旗上周五将AMD评级从中性上调至买入，目标价从460美元上调至575美元。值得注意的是，苹果早在2024年就开始推进\"LLM in a Flash\"端侧方案。这一布局背后，是愈演愈烈的DRAM供给危机。据TrendForce数据，高带宽内存（HBM）已占全部DRAM晶圆产能的约四分之一，DRAM合约价格在2026年第一季度单季环比暴涨约90%。Citrini Research指出，AI存储需求已大到需要多层架构共同承接，闪存并非取代HBM，而是在容量维度承接溢出需求——这场架构重构正在重新定价整条AI存储产业链。内存税危机：瓶颈从AI蔓延至全经济据摩根士丹利分析师Shawn Kim团队本月早些时候的判断，内存价格飙升和供应稀缺正演变为数字经济的全面风险，\"从AI基础设施的瓶颈，蔓延至硬件利润率、设备可负担性、云成本、通胀乃至政策层面。\"这一压力已有具体案例佐证：Xbox首席执行官Asha Sharma上周表示，内存成本在过去两年间上涨了约五倍，导致公司无法生产消费者所需数量的游戏主机。HBM对DRAM产能的持续蚕食是这场危机的核心驱动。据TrendForce及三星、SK海力士、美光等厂商的披露数据，HBM在DRAM晶圆产能中的占比已从2020年的2%攀升至2026年预估的25%。超大规模云厂商以多年期合同预购未来晶圆产出，进一步压缩了面向手机和PC的标准芯片可用产能。新增DRAM产能的建设同样面临结构性制约。扩产依赖EUV光刻机印制更精细线宽，每台EUV设备售价高达约2亿美元，一座新晶圆厂的投资动辄数百亿美元，建设周期在顺利情况下也需数年。这一供给刚性，正是本轮短缺具备持续性的根本原因。55倍成本差：闪存替代的经济逻辑据Citrini Research测算，闪存的每比特成本约为DRAM的1/55——QLC NAND约为每GB 0.05美元，DDR5 DRAM约为2.75美元，HBM3E则高达15美元。这一价差的可利用空间，在于AI推理中最大的单一内存消耗——KV缓存（记录模型每次生成步骤中所有先前标记的上下文，长对话中可增长至数百GB）——对读取速度的要求远低于模型权重的解码路径。对于此类顺序读取数据，DRAM的速度优势大幅收窄，而闪存的容量优势则充分体现。闪存的扩容路径也与DRAM存在本质区别。闪存通过垂直堆叠更多单元层来增加容量，依赖现有工厂已有的沉积和刻蚀工艺，无需新的光刻节点，不占用EUV资源。闪存控制器基于成熟的6/7纳米制程生产，远离正在制约先进制程的瓶颈节点。苹果研究人员此前发表的论文\"LLM in a Flash\"提供了方法论支撑：通过将大语言模型参数存储于设备闪存、按需调取至DRAM的方式，可在DRAM容量受限的设备上运行超出其容量上限的模型，并在CPU和GPU上分别实现比朴素加载方式快4至5倍和20至25倍的推理速度。两条路径：数据中心与端侧同步演进AMD的收购聚焦数据中心场景。通过将MEXT技术整合至AMD数据中心产品组合，AMD寻求帮助企业客户在AI工作负载部署中提升资源利用效率并压缩成本。摩根士丹利Shawn Kim团队认为，尽管内存短缺持续，AMD在云端市场竞争格局上仍具结构性优势——\"代理式AI驱动的CPU需求在结构上有利于AMD在云端市场份额的扩张。\"花旗对AMD的乐观预判则更多基于其GPU销售与英伟达的正面竞争态势。苹果的路径则落子端侧。\"LLM in a Flash\"方案将模型推理对昂贵云端内存的依赖部分转移至设备本地闪存，在降低云端运算成本的同时，为端侧AI应用提供可行的内存架构支撑。据Citrini Research，两大路径共同指向同一结论：AI推理的内存层级正在重构，低频KV缓存、模型权重及端侧数据，将逐步从高价的HBM/DRAM下沉至NAND Flash/SSD层，形成多层次存储架构。这一架构转变正沿产业链形成多层次的传导效应。据Citrini Research梳理，最直接的受益层是NAND原厂，高容量NAND、企业级SSD及QLC NAND为最纯粹的方向，包括SanDisk、西部数据、美光及铠侠。SSD控制器层被认为持续性最强——让闪存真正接近内存体验的核心在于控制器、固件与NVMe架构优化，涉及Silicon Motion、Marvell等。CXL/PCIe高速互联层亦受益。","news_type":1,"symbols_score_info":{"AMDS":0.6,"AAPX":0.6,"AAPL":1.89,"AMYY":0.6,"AMDY":0.6,"AMDL":0.6,"DAMD":0.6,"AAPB":0.6,"AMDU":0.6,"AAPD":0.6,"AMDG":0.6,"AMDW":0.6,"AAPW":0.6,"AMUU":0.6,"AAPY":0.6,"APLY":0.6,"AMD":1.96,"AMDD":0.6,"AAPU":0.6}},"isVote":1,"tweetType":1,"viewCount":1185,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}]}