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Nvidia Passes $3 Billion in First Quarter Revenue

The need for more processing power to render video games, mine digital currencies, and train machine learning programs to sort through medical images and plot paths for autonomous cars pushed Nvidia’s revenue in the first quarter up 10 percent from the previous quarter and 66 percent over the last year.

On Thursday, the Santa Clara, California-based company said that it pulled in $3.21 billion in the first quarter, up from $1.94 billion in the first quarter of 2018 and $2.91 billion in the fourth quarter of 2018. Sales related to data centers, where Nvidia’s graphics chips are used as accelerators for machine learning, totaled $701 million, up 71 percent over the last year.

“Nvidia had another record quarter with growth in all segments of the business,” said Ryan Shrout, principal analyst for Shrout Research, a technology research and consulting firm. “Data center gets the most attention with the company’s momentum and emphasis on machine learning and clearly that is paying off.”

More than half of Nvidia’s revenue still stems from its gaming business, which was down one percent from last quarter but up 68 percent over the last year, to $1.72 billion. The results from its automotive segment, which sells chips for driverless car prototypes, have largely stalled at $145 million, only $5 million over what it reported a year ago.

Nvidia continues to piggyback on the recent boom in digital currencies. Prospectors use battalions of graphics chips to handle the repetitive operations that mint new units of currencies like Ethereum and Bitcoin. The company reports that revenue in its OEM and IP business unit, which pulled in $387 million in the first quarter, up 115 percent quarter-over-quarter and 148 percent year-over-year.

“At the heart of our opportunity is the incredible growth of computing demand of A.I., just as traditional computing has slowed,” said Jensen Huang, chief executive of Nvidia, which forecast revenue of $3.10 billion in the second quarter. “The GPU computing approach we have pioneered is ideal for filling this vacuum.”

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