Nvidia: The AI Stack Is Changing

Qualcomm's $3.9 billion modular acquisition and OpenAI's Jalapeño chip introduce credible long-term challenges to Nvidia's CUDA software ecosystem.

U.S. data center electricity demand is projected to rise from 167 TWh to 376 TWh by 2030, making power infrastructure AI's next bottleneck.

SK Hynix's $28 billion Nasdaq IPO and Rubin production cuts highlight HBM supply, rather than GPUs, as AI's critical constraint.

Nvidia trades at just 23x forward earnings despite expected FY2027 revenue of $393 billion and FY2028 revenue approaching $559 billion.

Although custom silicon adoption is accelerating, overwhelming AI demand, strong profitability, and nearly 50% consensus upside continue supporting the long-term thesis.

Since my last coverage, Nvidia (NVDA) is down about 6% due to a drop in the AI narrative owing to fears regarding custom silicon, CUDA alternatives, and infrastructure constraints.

I believe the market is confusing This article was written by Yiannis Zourmpanos 17.34K Followers Follow Hi, I'm Yiannis.

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