For the better part of three years, the AI narrative has been synonymous with Nvidia (NASDAQ: NVDA). Their GPU roadmap—stretching from the current Hopper and Blackwell architectures to the anticipated Rubin series—has provided the essential scaffolding for the generative AI boom.
However, the spotlight is broadening. Micron Technology (NASDAQ: MU) has recently emerged as a favorite among analysts, following a trajectory that looks remarkably similar to Nvidia’s early ascent.
Understanding Micron’s Role in the AI Ecosystem
The AI hardware sector is composed of several distinct layers:
- General-Purpose GPUs: Companies like Nvidia and AMD produce versatile hardware designed for high-speed data processing.
- Custom Silicon (ASICs): Broadcom leads the way in specialized chips, which tech giants like Meta and Alphabet use for hyper-specific deep learning tasks.
- The Memory Essential: This is where Micron shines. As AI models grow in complexity, they require massive amounts of High-Bandwidth Memory (HBM), DRAM, and NAND storage to function.
Bloomberg Intelligence projects the AI accelerator market will hit $604 billion by 2033, growing at a 16% CAGR. This secular shift is a massive tailwind for Micron, which dominates the memory landscape. While Micron’s addressable market was roughly $35 billion in 2025, leadership expects that figure to nearly triple to $100 billion by 2028. Interestingly, the demand for memory is currently outpacing the growth of the GPU market itself.
The Surge in Memory Pricing
Why are memory costs skyrocketing? The answer lies in the aggressive capital expenditure of “hyperscalers.” Big Tech is on track to pour over $500 billion into AI infrastructure this year alone. This spending spree has triggered a severe shortage of HBM. Consequently, TrendForce predicts that prices for DRAM and NAND could spike by 60% and 38% respectively in just the first quarter, significantly boosting the profit margins for suppliers like Micron.
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