Memory chips such as DRAM have historically followed sharp boom-and-bust cycles. Today, however, they are anchoring themselves to a far more structurally stable growth engine: artificial intelligence (AI). Leading suppliers including SK Hynix, Samsung Electronics, and Micron are repositioning memory not as a commodity, but as a strategic enabler of generative AI.
Samsung CFO Kim Woo-hyun recently summarized this shift, stating that Samsung aims to become a comprehensive AI memory provider by driving architectural change and delivering customized solutions.
High Bandwidth Memory (HBM) now sits at the heart of modern AI accelerators. When paired with GPUs such as NVIDIA’s H100, HBM enables the massive data throughput required by large language models (LLMs). Systems like ChatGPT rely on high-performance memory to store context, parameters, and intermediate results, making memory capacity and bandwidth as critical as raw compute.
Demand has surged so rapidly that AI companies are struggling to secure sufficient supply. OpenAI CEO Sam Altman recently visited South Korea to meet with executives from SK Hynix and Samsung, followed by discussions with Micron, underscoring how central HBM has become to the AI value chain.
🥇 SK Hynix’s Early HBM Lead #
SK Hynix’s advantage in AI memory can be traced back to 2015, when it launched its first HBM product ahead of Samsung. That early bet allowed the company to build deep expertise serving high-speed computing markets, including gaming GPUs and data center accelerators.
HBM achieves its performance by vertically stacking multiple DRAM dies and connecting them with ultra-wide interfaces, dramatically increasing bandwidth compared to traditional DRAM. This architecture has made HBM indispensable for generative AI and high-performance computing workloads.
Key indicators of SK Hynix’s lead include:
- Market Momentum: Sales of HBM3 chips grew more than fivefold year-over-year in 2023.
- Secured Demand: According to The Digital Times, NVIDIA has paid $540–770 million in advance to SK Hynix and Micron to lock in future HBM supply for its GPUs.
Next-Generation HBM Roadmap #
SK Hynix is simultaneously advancing two critical product lines: mass production of HBM3E and development of HBM4.
- HBM3E: Compared to HBM3, HBM3E delivers substantially higher bandwidth, reaching up to 1.15 TB/s. NVIDIA plans to pair its H200 and B100 GPUs with six and eight HBM3E stacks, respectively.
- HBM4: Expected around 2025, HBM4 represents a major architectural shift. It enables direct stacking of memory on top of the processor, removing intermediate layers and fundamentally changing chip design, packaging, and manufacturing workflows.
⚔️ Intensifying Competition #
Samsung Electronics positions HBM3E as a flagship AI memory product and claims strong technological competitiveness. Both Samsung and Micron have prepared HBM3E devices and are undergoing qualification by major AI customers, including NVIDIA.
Still, many analysts believe SK Hynix maintains a timing and execution advantage:
- Pure-Play Focus: Unlike Samsung, which operates across memory, logic, and consumer electronics, SK Hynix is a pure-play memory supplier, allowing tighter focus on HBM optimization.
- Samsung’s Scale and Ambition: Samsung continues to invest aggressively in AI memory R&D. At CES 2024, Samsung Electronics’ CEO publicly committed to doubling the company’s market capitalization within three years, with AI memory positioned as a key driver.
South Korea, home to the world’s two largest memory manufacturers, is positioning itself as a core hub of the global AI supply chain. At the center of this strategy lies HBM, a component that has quietly evolved from a niche technology into one of the most critical bottlenecks—and opportunities—of the AI revolution.