Nvidia, one of the biggest producers of graphics processing units (GPUs), reported a 265% year-on-year increase in revenue amid rising global demand for artificial intelligence (AI) equipment. 

According to the latest fourth-quarter financial results, Nvidia recorded revenue of $22.1 billion in Q4, up 22% from Q3 and 265% from the prior year. Jensen Huang, founder and CEO of Nvidia, attributed the drive in sales to the surge in the global demand for accelerated computing and generative AI. The chipmaker currently boasts a market capitalization of $1.67 trillion.

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Nvidia’s Q4 fiscal 2024 summary shows a quarterly growth of 22% and a YoY growth of 265%. Source: investor.nvidia.com

The results come as Nvidia overtook Elon Musk’s Tesla as Wall Street’s most-traded stock. About $30 billion worth of Nvidia shares were moved among traders in the last 30 trading sessions, which averaged roughly $22 billion for Tesla in the same timeframe, according to a Reuters report.

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Nvidia overtakes Tesla to become the most-traded stock, 30-day average turnover. Source: LSEG (created by Reuters)

On Jan. 27, Musk confirmed Tesla’s plan to spend more than $500 million to procure AI hardware from Nvidia in 2024 alone. He said:

The table stakes for being competitive in AI are at least several billion dollars per year at this point.

Tesla also has plans to buy AI-related hardware from Nvidia’s biggest GPU-manufacturing competitor, AMD.

The Nvidia RTX series, first introduced in September 2018, is seen as a go-to platform for generative AI enthusiasts, gamers and creators. In Q3 2023, Nvidia recorded a revenue of $18.1 billion, supported by a strong market cap of $1.2 trillion.

In December 2023, Yann LeCun, the chief AI scientist for Facebook AI Research at Meta, acknowledged Nvidia’s current dominance in the AI hardware industry. He further said that the chip manufacturer is fueling the AI war:

I know (Nvidia CEO) Jensen. There’s an AI war, and he’s supplying the weapons.

On the other hand, LeCun criticized the extended use of text-based models to train generative AI systems. “Text is a very poor source of information,” he said, adding, “Train a system on the equivalent of 20,000 years of reading material, and they still don’t understand that if A is the same as B, then B is the same as A.”


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