Core Viewpoint - The article highlights the significance of High Bandwidth Memory (HBM) technology, particularly HBM4, as a critical component for next-generation AI systems, addressing memory bottlenecks and enhancing performance for AI workloads [1][2]. Group 1: HBM4 Technology Overview - HBM4 represents a fundamental shift in memory architecture by integrating logic chips into memory stacks, allowing for pre-processing of data before it reaches the main AI processor [2]. - The development of HBM4 aims to significantly improve bandwidth, energy efficiency, and system-level customization capabilities for AI accelerators and data center workloads [1]. Group 2: Key Players and Developments - SK Hynix, a leader in the HBM market with over 50% share, introduced a 48GB 16-layer HBM4 device capable of exceeding 2TB/s bandwidth, with mass production planned for Q3 2026 [3]. - Samsung is focusing on a full-process solution for HBM4, producing logic chips in-house and utilizing hybrid bonding technology to enhance performance and reduce height [4][5]. - Micron is expanding its production capacity for 36GB 12-layer HBM chips and aims to achieve a dedicated wafer capacity of 15,000 wafers by the end of 2026 [6]. Group 3: Market Dynamics and Competition - The competition among HBM manufacturers is intensifying, with NVIDIA's Rubin GPU platform driving demand for HBM4, as it is expected to be one of the first exclusive users of HBM4 devices [2]. - Reports indicate that NVIDIA has revised its HBM4 specifications, increasing single-pin speed requirements to over 11Gbps, prompting manufacturers to enhance their designs [6].