AI需求创造突破口 NAND正在从周期品重新变成AI基础设施的关键部件，需求端的结构性变化抬升了价格与估值，也把曾 被视为二线阵营的铠侠与闪迪推到聚光灯下。 随着AI工作负载从训练转向推理，SSD在AI数据中心的部署扩大，数据中心对NAND闪存的采购规模激 增，为非传统领先厂商创造了市场机遇窗口。 铠侠与闪迪维持了超过25年的深度合作，通过合资与联合开发，双方共同分担昂贵设备与研发支出，以 规模效应摊薄成本。 在技术路线上，闪迪聚焦将HBF集成进英伟达、AMD与Google的产品。铠侠则更侧重SSD端的性能跃 迁。 市场重心分化，押注不同技术路线 市场重心上，据Knowing.asia报道，铠侠和闪迪两者的市场重心明显分化，铠侠主要向日本及全球大型 电子制造商供货，闪迪则主导消费存储市场，并在北美及海外企业级SSD领域占据强势地位。 技术路线上，HBM受限于容量与成本，NAND通过HBF（高容量近存储）与AI SSD（智能预处理）两 种技术路线优化AI架构。 据EE Times报道，随着AI工作负载从训练转向推理，SSD在AI数据中心的部署扩大，NAND因此迎来新 的需求推力。 对投资者而言，这意味着NAND ...

Investment Rating - The report maintains a "Positive" investment rating for the electronic industry, specifically focusing on NAND and SSD sectors driven by AI demand [6]. Core Insights - AI applications are expected to drive a rapid increase in SSD usage, leading to a prolonged boom cycle for both SSD and NAND markets [3][10]. - The global data volume is projected to grow significantly, with active data becoming a larger portion due to AI model applications [19][31]. - The demand for SSDs is anticipated to rise sharply as they meet the high throughput requirements for active data in data centers, surpassing traditional HDDs [10][34]. Summary by Sections 1. AI - The application of AI models is expected to significantly increase the proportion of active data, transforming previously dormant data into frequently accessed data [21][22]. - By 2030, it is estimated that 100% of hot data will be stored on SSDs, reflecting a shift in data storage paradigms [22]. 2. SSD - SSDs are favored for their high read/write speeds and ability to handle high workloads, making them suitable for active data storage in data centers [34][40]. - The power efficiency of SSDs is a significant advantage, especially as data center power demands increase [48][51]. - AI training and inference are driving the development of AI SSDs, which require high performance, large capacity, and energy efficiency [54][56]. 3. NAND - The NAND market is expected to experience a prolonged period of supply-demand imbalance, with limited capital expenditure from leading manufacturers [10][11]. - The concentration of the global NAND market is high, with major players like Samsung, Micron, and SK Hynix focusing on high-bandwidth memory (HBM) rather than expanding NAND production [10][11]. 4. Enterprise SSD - The report highlights several key companies in the semiconductor and storage sectors that are well-positioned to benefit from the ongoing trends, including domestic semiconductor equipment manufacturers and storage module companies [3][13].

Core Insights - The "MTS2026 Storage Industry Trend Seminar" and the release of the "2026 Top Technology Market Trends Forecast" were successfully held in Shenzhen, gathering over a thousand industry elites and analysts, highlighting the industry's keen interest in future trends [1][37] - The impact of AI on the storage industry was emphasized, with a focus on real demand and significant changes in the high-tech manufacturing supply chain [1] Group 1: Industry Growth and Trends - TrendForce forecasts a 19% annual growth in the wafer foundry industry for 2026, with AI-related demand driving advanced process markets to a remarkable 28% growth [5] - The global data volume is expected to grow at a compound annual growth rate of approximately 40%, necessitating higher performance from data centers [7] - AI servers and general servers are driving a new super cycle in memory, with AI and server-related applications projected to account for 66% of DRAM total capacity by 2026 [17] Group 2: Technological Innovations - Intel's new Xeon 6 series processors are positioned as the preferred choice for global AI servers, featuring performance enhancements and innovative architectures to support AI workloads [7][8] - Solidigm is leading the QLC product market and has introduced high-performance PCIe 5.0 SSDs to meet the demands of AI workloads, enhancing storage efficiency and performance [20] - The introduction of HBF (High Bandwidth Flash) and AI SSDs is expected to reshape the NAND industry value, addressing storage bottlenecks caused by the explosion of LLM parameters [34] Group 3: Market Dynamics and Competitive Landscape - The competition in the AI server market is intensifying, with major players like NVIDIA and AMD leading the GPU AI market, while Chinese companies are increasingly focusing on self-developed ASICs [29] - The memory market is anticipated to face severe shortages, with DRAM ASP expected to rise by 36% in 2026, leading to a projected 56% increase in DRAM revenue [17] - The demand for advanced packaging technologies is growing, with companies like 时创意 adopting innovative processes to meet the requirements of AI-driven applications [13][14]

Core Insights - The article discusses the trends and predictions for the semiconductor and storage industries, emphasizing the impact of AI on market dynamics and technology advancements [4][10][17]. Group 1: AI and Semiconductor Industry Trends - The wafer foundry industry is expected to grow by 19% in revenue in 2026, with AI-related demand driving advanced process markets to a remarkable 28% growth [10]. - TSMC has begun production using 2nm technology and plans to advance to 1nm processes, indicating a significant technological shift in the semiconductor sector [10]. - The demand for AI chips is expected to surge, with major cloud providers launching their own AI chips, highlighting the competitive landscape in the semiconductor market [10]. Group 2: AR Glasses and AI Integration - AI and AR glasses are forming a symbiotic relationship, enhancing user interaction and accelerating data accumulation for large language models [12]. - The global shipment of AR glasses is projected to exceed 10 million units by 2030, driven by major brands like Google and Apple entering the market [13]. - China plays a crucial role in the AR glasses market, with significant contributions in manufacturing and supply chain integration [14]. Group 3: Memory Market Dynamics - AI servers and general servers are driving a new super cycle in the memory market, with AI applications expected to account for 66% of DRAM capacity by 2026 [17]. - The DRAM market is anticipated to face severe shortages, with prices expected to rise significantly, leading to a projected 56% increase in DRAM revenue in 2026 [17]. - The competition for limited DRAM capacity is intensifying, particularly as AI server demands begin to outstrip supply for consumer devices [17]. Group 4: Server Market Outlook - Global server shipments are expected to grow by over 9% in 2026, with AI servers leading this growth at over 20% [20]. - The competition in the AI server market is intensifying, with major players like NVIDIA and AMD dominating the GPU AI market while Chinese companies pursue self-developed ASIC solutions [20]. Group 5: Power Semiconductor Transformation - The demand for power semiconductors is shifting due to AI, with SiC and GaN technologies becoming critical for high-voltage power supply architectures [22]. - SiC technology is establishing a leadership position in high-voltage applications, while GaN is entering a rapid growth phase across multiple applications, including AI data centers [22][24]. Group 6: NAND Flash Market Innovations - The AI boom is creating storage bottlenecks, leading to a shift towards high-density QLC eSSD due to limited supply in traditional HDD markets [27]. - New NAND Flash technologies are emerging, such as HBF and AI SSD, which aim to enhance performance and address storage challenges in AI applications [27]. - The NAND Flash industry is expected to thrive amid ongoing supply shortages, with innovations reshaping its value proposition [27].

Core Viewpoint - The article discusses the challenges faced by large language models (LLMs) due to the "memory wall" issue and proposes SSD-based storage offloading technology as a new path for efficient AI model operation [1]. Group 1: Industry Insights and Investment Recommendations - The massive data generated by AI is impacting global data center storage facilities, leading to a focus on KV Cache caching that can offload from GPU memory to CPU and SSD [1]. - The traditional Nearline HDD, which has been a cornerstone for massive data storage, is experiencing supply shortages, prompting a shift towards high-performance, high-cost SSDs, resulting in an "overweight" rating for the industry [1]. Group 2: KV Cache Technology and Its Implications - The growth of KV Cache capacity is exceeding the capabilities of HBM, as it temporarily stores generated tokens to optimize computational efficiency and reduce redundant calculations [2]. - As the demand for larger models and longer sequences increases, the reliance on HBM is becoming a bottleneck, leading to frequent memory overflows and performance issues [2]. Group 3: Technological Developments in Storage Solutions - The industry is exploring tiered caching management technologies for KV Cache, with NVIDIA launching a distributed inference service framework called Dynamo to offload KV Cache from GPU memory to CPU, SSD, and even network storage [3]. - Samsung has proposed an SSD-based storage offloading solution to address the "memory wall" challenge, which can reduce the first token latency by up to 66% and inter-token latency by up to 42% when KV Cache size exceeds HBM or DRAM capacity [3]. Group 4: Market Trends and Supply Chain Dynamics - The demand for AI storage is driving a replacement effect for HDDs, with NAND Flash suppliers accelerating the production of large-capacity Nearline SSDs due to significant supply gaps in the HDD market [4]. - NAND Flash manufacturers are investing in the production of ultra-large capacity Nearline SSDs, such as 122TB and even 245TB models, to meet the growing demand from AI inference applications [4].

Group 1: Semiconductor Sector Insights - The "14th Five-Year Plan" focuses on domestic key core technology areas, with equipment being a direct beneficiary. Short-term AI computing power demand is driving expansion among domestic and foreign logic and storage chip manufacturers, leading to strong demand for etching and thin film deposition equipment. Long-term, the localization process under the "14th Five-Year Plan" technology self-reliance strategy is more solid [1] - The semiconductor supercycle is expected to be driven by general artificial intelligence, with a forecast of a 100,000-fold increase in total computing power by 2035. Continuous optimism for AI driving the semiconductor supercycle across the entire industry chain, with key stocks including SMIC, Hua Hong Semiconductor, and Cambrian [2] - AI-generated massive data is impacting global data center storage facilities, leading to a significant supply shortage of Nearline HDDs. This is prompting flash memory manufacturers to accelerate the production of ultra-large capacity Nearline SSDs, making high-performance SSDs a market focus [3] Group 2: Storage Market Dynamics - AI demand is significantly increasing storage needs, resulting in a substantial rise in storage prices. The transition of storage manufacturers to HBM, DDR5, and large-capacity NAND is causing higher price increases for DDR4 and small-capacity NAND, further driving up storage prices due to downstream stockpiling demand. The storage market's favorable conditions are expected to persist due to strong growth in AI computing power demand [4] - The technology sector, represented by AI, is expected to continue leading the market. Companies like Haiguang Information and Cambrian have reported significant performance increases, with ample inventory reserves, indicating a sustained high growth trend for the year [5]

Core Insights - The performance of some GPUs is hindered by insufficient storage speed, leading to underwhelming application results and overall efficiency limitations [2][3] Group 1: Storage and GPU Performance - The main issue affecting GPU performance is the waiting time for storage data, which results in resource wastage and restricts efficiency improvements [2] - The demand for storage solutions is increasing as the pace of computational power development accelerates [2] - New AI scenarios will require SSDs to adopt GPU direct scheduling methods to achieve high throughput and performance [2] Group 2: Market Trends and Innovations - Companies like 英韧科技 are focusing on enterprise-level storage solutions tailored for AI applications, aligning with international trends [2] - Recent product launches include "AI SSD" by 铠侠 and ultra-high-speed products by 三星 and 海力士, designed to meet the demands of AI GPU data scheduling [2] Group 3: Technical Requirements for AI SSDs - Key performance indicators for storage in data centers include high IOPS, low latency, and QoS, which define storage capabilities from efficiency, response speed, and stability perspectives [3] - The construction of AI SSDs requires three main elements: media with low latency and high transfer efficiency, high-speed interfaces and protocols, and a simple yet efficient architecture [3] Group 4: Competitive Product Development - 英韧科技's latest Dongting-N3X series utilizes PCIe Gen5 interface and new XL-Flash media to meet current AI SSD application demands [4] - Future product iterations are planned, with expectations to reach 10M IOPS by 2026 and 25-50M IOPS by 2027, along with the integration of NVMe and CXL protocols [4]

Investment Rating - The report maintains a positive outlook on the industry, particularly highlighting the growth potential in AI-driven sectors and advanced memory technologies [12][22]. Core Insights - The report emphasizes the significant growth in the AI application landscape, with notable advancements from companies like Alibaba and DeepSeek, showcasing their competitive models [11][12]. - Micron Technology reported a record revenue of $11.3 billion for FY25Q4, driven by strong demand in data centers and a focus on high-value products like HBM and AI SSDs [12][22]. - OpenAI is expanding into the hardware sector, collaborating with key suppliers to develop consumer-grade AI devices, indicating a strategic shift towards integrated AI solutions [23]. Summary by Sections AI Application Growth - Gemini's activity has seen a substantial increase, while domestic applications like Doubao are also growing steadily [9][11]. - Alibaba's Qwen3-Omni and Qwen3-Max models have achieved significant benchmarks, outperforming competitors in various tests [11]. Micron Technology Performance - Micron's FY25Q4 revenue reached $11.3 billion, a 46% year-over-year increase, with data center revenue accounting for 56% of total sales [12][18]. - HBM has become a core growth driver, with Q4 HBM revenue nearing $2 billion, and the company is on track to maintain its market share in DRAM [15][22]. - The company plans to increase capital expenditures to $18 billion in FY26, focusing on DRAM and HBM production [18][22]. OpenAI's Hardware Strategy - OpenAI is developing a pocket-sized AI device in collaboration with key suppliers, aiming to create a new category of "AI companion" devices [23]. - The initiative reflects a broader strategy to reduce reliance on cloud services and enhance user privacy, although it faces challenges in energy efficiency and market acceptance [23].

Core Viewpoint - Kioxia plans to commercialize AI SSDs by 2027, with data reading speeds nearly 100 times faster than traditional products [1] Group 1: Product Development - Kioxia is collaborating with NVIDIA to develop SSDs for generative AI computing servers, aiming to partially replace HBM as GPU memory expanders [1] - The first samples of the new SSDs are expected to be released in the second half of 2026, based on NVIDIA's proposals and requirements [1] Group 2: Market Forecast - Kioxia predicts that by 2029, half of the NAND chips will be purchased by AI-related industries [1] Group 3: Performance Specifications - NVIDIA has set a target reading performance of 200 million IOPS, which Kioxia plans to achieve through the collaboration of two SSDs [1] - The SSDs will support the PCIe 7.0 standard, representing a next-generation standard [1]

Market Overview - US stock indices experienced slight gains, with the Dow Jones up 0.32%, S&P 500 up 0.24%, and Nasdaq up 0.21% [5] - Major tech stocks mostly rose, with Intel increasing over 2%, while Chinese concept stocks fell, with the Nasdaq Golden Dragon China Index down 2.58% [5] - International oil prices saw minor increases, with WTI crude oil rising 0.96% to $63.86 per barrel and Brent crude oil up 0.76% to $67.21 per barrel [7] Company Developments - Huawei launched three new AI SSD products, achieving the industry's largest single-disk capacity of up to 245 TB, aimed at enhancing AI business experiences [20] - Meituan reported Q2 revenue of 918 billion yuan, a year-on-year increase of 11.7%, but anticipates significant losses in its "core local business" for Q3 due to high competition [24] - Chipmaker Cambrian Technology's stock price surged, reaching a peak of 1464.98 yuan, surpassing Kweichow Moutai to become the new "stock king," with a staggering revenue increase of 4347.82% year-on-year [23] - Chery Automobile received approval for its IPO and the full circulation of its unlisted shares, aiming to raise funds and enhance market liquidity [25] Industry Insights - The Chinese government is promoting the development of the satellite communication industry, with plans to improve management systems and expand market applications by 2030 [11][12] - The Jiangsu Free Trade Zone's biopharmaceutical innovation plan aims for rapid growth and modernization of the industry by 2030, focusing on key areas like large molecule drugs and gene therapy [9] - The market for digital imaging services in Guizhou Province is seeing a shift towards bundled procurement, with a focus on service-oriented contracts [16] Financial Performance - Wuliangye reported a slight increase in revenue and net profit for the first half of 2025, with revenue at 527.71 billion yuan, up 4.19% year-on-year, marking the first single-digit growth in a decade [33]