Net income increased more than seven times from a year ago, jumping to $14.88 billion in the first quarter ended April 28 from $2.04 billion a year earlier. Sales more than tripled to $26.04 billion from $7.19 billion the previous year.
“The next industrial revolution has begun,” CEO Jensen Huang declared on a conference call with analysts. Huang predicted that companies acquiring Nvidia’s chips would use them to build a new type of data center, which he called an “AI factory,” to produce “a new product, artificial intelligence.”
Huang said AI models will now be “multimodal,” meaning they can understand text, audio, images, video, and 3D data, and will also be able to “reason and plan,” making the training process faster. He added that it is becoming more and more.
The company reported earnings per share (adjusted to exclude one-time items) of $6.12, well above the $5.60 Wall Street analysts had expected, according to FactSet. The company also announced a 1-for-10 stock split, which the company noted would make the company’s shares more accessible to employees and investors. It also increased its dividend to 10 cents from 4 cents a share. Nvidia’s shares rose 6% to $1,006.89 in after-hours trading. The stock has risen more than 200% over the past year. The Santa Clara, California-based company built an early lead in the hardware and software needed to tailor its technology to AI applications, in part because founder and CEO Jensen Huang began pushing into a company that was then seen as only half-baked in technology more than a decade ago. It also makes chips for games and cars.
The company currently has the third-highest market value on Wall Street, behind Microsoft and Apple.
“NVIDIA has defied gravity once again,” eMarketer analyst Jacob Born said of the quarterly report. Many tech companies are trying to reduce their dependence on Nvidia, which has achieved a level of AI hardware dominance comparable to pioneering computing companies like Intel, but “we’re not there yet,” he said. added.
Demand for generative AI systems that can write documents, create images and act as increasingly lifelike personal assistants has driven astronomical sales of Nvidia’s dedicated AI chips over the past year. Tech giants Amazon, Google, Meta and Microsoft have all signaled they will need to invest more in the chips and data centers needed to train and operate their AI systems in the coming months.
What happens after that may be another matter. Some analysts believe the race to build the biggest data centers will eventually peak, and that the aftermath could create trouble for Nvidia.
“The biggest question remaining is the length of this runway,” Third Bridge analyst Lucas Kaye wrote in a research note. AI workloads in the cloud, he said, will eventually move from training AI models to inference, or the more mundane tasks of using already trained AI systems to process fresh data. I pointed it out. Also, for inference he doesn’t need the level of power that Nvidia’s expensive top-of-the-line chips provide. This opens up a market opportunity for chip manufacturers that offer lower-performance but lower-cost alternatives.
If that happens, Keh wrote, “NVIDIA’s dominant market share position will be put to the test.”
