Jensen Huang Told CES 2026 That Memory Is Now the Biggest Bottleneck in AI. Micron and Sandisk Have Outperformed Nvidia's Stock Ever Since.

Yahoo Finance ·

CES, held annually in January, is one of the most important trade shows where tech companies go to unveil innovations and showcase bold ideas for the future. At the 2026 event, Nvidia CEO Jensen Huang offered something that has been just as impactful: his insights about the growing memory needs of artificial intelligence (AI). And based on where the stock prices of Micron Technology ( MU +0.04% ) and Sandisk ( SNDK 3.99% ) have gone since then, his understand of the situation was right on the money. Nvidia CEO Jensen Huang. Image source: Nvidia. Large language models are being asked to deliver on requests promptly, but there's also a growing expectation that these tools will preserve users' older requests and conversations as time savers to provide context for the new ones. That requires increasingly higher memory capacity in the data centers that power those AIs, which Huang alluded to in his January CES speech: We would like this AI to stay with us our entire lives and remember every single conversation we've ever had with it, right? Every single lick of research that I've asked for. Of course, the number of people sharing the supercomputer will continue to grow. And so, this context memory, which started out fitting inside an HBM, is no longer large enough. Over the last year, as Micron and Sandisk have kept reporting surging revenue figures in their respective quarterly reports, Huang's insight on the expanding demand for memory and storage for AI has proven true.

AI 시장 분석

At CES 2026, CEO Jensen Huang identified memory shortages as the primary bottleneck for AI, signaling a surge in demand for high-capacity memory in data centers. Subsequently, Micron and Sandisk reported rapid earnings growth, outperforming NVDA in stock returns. This suggests that memory semiconductor companies have emerged as key beneficiaries of AI infrastructure expansion.

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DYAX 전담 분석

The shift in AI hardware focus from processing power to memory capacity highlights the limitations of existing architectures. As AI models scale, the need for faster, high-density data retrieval becomes critical, positioning memory chipmakers as essential components of the AI supply chain. The strong performance of Micron and Sandisk reflects this structural shift in investor preference toward hardware essential for operationalizing AI.

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