Summary of Key Points from the Conference Call Industry and Company Involved - The discussion centers around **NAND Flash** demand influenced by **NVIDIA's new architecture** and its implications for the **AI era** [1][2][3][4]. Core Insights and Arguments - NVIDIA's new architecture offloads KV Cache data to NAND Flash, addressing the capacity limitations of HBM and DDR memory, thereby enhancing GPU performance [1][3]. - Each GPU is projected to require an additional **16TB of NAND Flash**, leading to an estimated increase in NAND Flash demand of **13.6 billion GB** if NVIDIA's total shipment reaches **8 million units**. This represents a **15% increase** compared to the current total supply of **92.5 billion GB** [1][3]. - The demand increase is expected to materialize in **2026-2027**, with similar calculations applicable to ASIC cards [1][3]. - The AI era is anticipated to drive sustained growth in NAND Flash demand, influenced by the relationship between GPUs or ASICs and NAND Flash, as well as the storage needs generated by multimodal generative technologies [1][4]. Additional Important Content - The introduction of NVIDIA's inference context storage platform at the **2026 CES** is a significant development, as it integrates NAND Flash into memory solutions, further clarifying demand estimations for NAND Flash [3]. - The rise of large models in AI will necessitate the storage of extensive user interaction data in NAND Flash, contributing to the overall demand growth [4]. - The expected **15% increase** in NAND Flash demand, as illustrated by the NVIDIA Ruby series, underscores the growing reliance on efficient storage solutions in the AI landscape [2][4].