Goldman Sachs analysts believe that the computing power of AI accelerators far exceeds the data transfer speed and capacity of memory, making memory bandwidth and capacity the main bottlenecks constraining the expansion of next-generation AI models.
According to reports, Goldman Sachs has comprehensively revised upward the supply-demand gaps for the three major markets of DRAM, NAND, and HBM in 2027, with the degree of supply tightness surpassing that of 2026, and the shortage is expected to persist until 2028.
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