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Nvidia Commits $500 Billion to Building AI Supercomputers in the U.S.

In a move that underscores the escalating race in artificial intelligence, Nvidia has announced a monumental investment plan to build AI supercomputers entirely within the United States. The company aims to pour up to $500 billion into this initiative, which aligns closely with the current administration’s push for domestic tech manufacturing and supply chain resilience.

As part of the plan, Nvidia will construct over one million square feet of advanced manufacturing space in Texas. The company is partnering with Taiwanese firms Foxconn and Wistron to carry out the production, with full operations expected to ramp up within 12 to 15 months. Nvidia’s strategy aims to reduce its reliance on overseas facilities, particularly those in Taiwan, where TSMC currently produces most of its chips.

The U.S. expansion comes at a critical time. The tech industry has faced increasing pressure due to global supply chain disruptions, geopolitical tensions, and rising tariffs. In response, major companies—including Apple, Microsoft, and Meta—have also announced significant investments to bolster their domestic operations.

Nvidia CEO Jensen Huang stated that the company’s U.S. production plans are not just about politics—they’re about meeting skyrocketing demand for AI infrastructure. As artificial intelligence becomes more embedded in everyday technology, the need for powerful, locally produced computing systems is greater than ever.

Despite reaching a peak valuation of nearly $3.4 trillion in 2024, Nvidia has since lost around $600 billion in market value. Analysts attribute this to increasing competition from Chinese AI firms such as DeepSeek, as well as investor concerns over trade policy volatility.

Nevertheless, Huang remains optimistic. He projects that data center revenue could reach $1 trillion by 2028, placing Nvidia at the forefront of the global AI boom. The company’s bold domestic expansion could serve as a blueprint for other tech giants looking to future-proof their operations.

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