US Tightens Grip on AI Technology: New Export Controls on Advanced Memory Chips

In a decisive move to maintain its technological edge, the US government has imposed new export restrictions on high-tech memory chips critical for artificial intelligence (AI) applications. These rules target both US-made and foreign-produced high bandwidth memory (HBM) chips, which have seen soaring demand amidst the global surge in AI technologies. HBM chips, which stack memory components to increase data storage and transmission speeds, are integral to various AI applications, including generative AI, powered by processors like Nvidia’s GPUs and AMD’s offerings.

HBM technology has emerged as a game-changer in the semiconductor industry, offering far superior performance compared to the older DRAM technology. By providing larger storage and faster data transmission, HBM chips enable smooth and efficient operation of AI systems, particularly those dealing with complex computations. “The processor and the memory are two essential components to AI. Without memory, it’s like having a brain with logic but no memory,” explained G Dan Hutcheson, a vice chair at TechInsights. These chips are used in high-performance computing, data centers, autonomous vehicles, and, most notably, AI-driven technologies that require massive data processing.

The new export controls, announced on December 2, are the latest in a series of restrictions aimed at preventing China from gaining access to advanced technologies that could enhance its military and technological capabilities. While these sanctions may slow China’s development of cutting-edge AI chips in the short term, experts suggest that China is steadily advancing its own HBM production. Companies like Yangtze Memory Technologies and Changxin Memory Technologies are increasing their production capacity to meet China’s long-term goal of technological self-reliance, though their capabilities still lag behind global leaders like SK Hynix, Samsung, and Micron.

What sets HBM chips apart from traditional memory chips is their ability to store vast amounts of data and transmit it at rapid speeds. These features are crucial for AI applications, which require high computational power to process large datasets without delay. The difference between HBM and older memory technologies can be likened to a highway: the broader the bandwidth (or the more lanes a highway has), the less likely there will be bottlenecks. As Hutcheson put it, “It’s like the difference between a two-lane highway and a hundred-lane highway. You just don’t get traffic jams.”

Currently, three companies dominate the global HBM market. As of 2022, South Korea’s Hynix controlled 50% of the market, followed by Samsung with 40%, and Micron at 10%. Hynix and Samsung are expected to maintain similar shares in the coming years, while Micron plans to expand its market share to 20-25% by 2025. The growing demand for HBM is reflected in its rising market value, which is set to exceed 20% of the total memory chip market by 2024, with projections suggesting it could surpass 30% by the following year.

Manufacturing HBM is no simple task. The chips are made by stacking multiple thin layers of traditional memory chips, much like a “hamburger” of technology. The precision required to achieve this design is immense, with each layer needing to be as thin as a strand of hair. This advanced packaging process, which includes drilling tiny holes for electrical connections, makes HBM production a highly specialized and expensive process. “You have a lot more failure points when you try to make these devices. It’s almost like building a house of cards,” Hutcheson noted. The complexity of this technology contributes to its high price, making HBM a key component in the ongoing global race for AI dominance.

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