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Nvidia Posts $215 Billion Annual Revenue, Fueled by Unrelenting AI Demand

Nvidia has reported a record $215.9 billion in annual revenue, a figure that underscores the company's dominance even as questions persist about the sustainability of artificial intelligence...

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Nvidia has reported a record $215.9 billion in annual revenue, a figure that underscores the company's dominance even as questions persist about the sustainability of artificial intelligence spending. The results, announced Wednesday, surpassed analyst expectations, with fourth-quarter sales alone surging 73% year-over-year.

Chief Executive Jensen Huang described a market where "computing demand is growing exponentially," with customers investing heavily in what he termed the "factories" for an AI-driven industrial revolution. As the world's most valuable public company, valued near $4.8 trillion, Nvidia supplies the critical chips powering AI developers like OpenAI and Meta.

Gene Munster of Deepwater Asset Management observed on social media that "AI is accelerating faster than people not using these tools can grasp," suggesting a prolonged expansion phase. However, some critics point to complex financing deals involving Nvidia investments, which they argue could obscure the true strength of underlying AI demand.

The company navigates significant geopolitical currents. While the administration of President Donald Trump recently permitted conditional sales of Nvidia's H200 chips to Chinese customers, a Commerce Department official this week stated no such chips have yet been sold. Nvidia's official outlook omitted specific revenue projections for China.

Beyond hardware, Nvidia is pushing into new frontiers. At the CES show last month, Huang introduced an open-source AI platform, "Alpamayo," designed to bring advanced reasoning to self-driving cars, and announced plans for a robotaxi service launching next year. The company is also fortifying its position through acquisition, having completed a $20 billion purchase of rival Groq to bolster its capabilities in AI inference, the next critical phase where trained models generate real-world answers.

Source: BBC News

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