In 2025, global AI chips focus on high-end HBM memory; NVIDIA's new Blackwell platform drives growth, amid geopolitical limits and steady AI server demand, with rapid HBM technology evolution toward HBM4 in 2026. High-end AI chips primarily use HBM memory;. In particular, industry experts expect SK hynix to be the primary anchor of this shift, as a chipmaker capable of delivering both HBM3E and next-gen HBM4 reliably. NVIDIA's. High Bandwidth Memory (HBM) for AI Servers by Application (CPU+GPU AI Servers, Others), by Types (HBM2, HBM2E, HBM3, Others), by North America (United States, Canada, Mexico), by South America (Brazil, Argentina, Rest of South America), by Europe (United Kingdom, Germany, France, Italy, Spain. As leading memory semiconductor manufacturers; Samsung Electronics Co. (KRX: 000660), and Micron Technology Inc. (NASDAQ: MU), divert production capacity toward high-bandwidth memory, a premium form of DRAM used in AI data centers, supplies of conventional DRAM are. Standards like Compute Express Link are emerging as critical tools for expanding memory capacity, enabling sharing, and improving efficiency, making memory hierarchy design a key factor in optimizing AI infrastructure and reducing costs. Ask an AI platform architect what breaks first at scale, and. AI-driven applications are fueling significant year-over-year growth in high-bandwidth memory (HBM).
