The artificial intelligence (AI) revolution has whetted the appetites of Nvidia Corp’s competitors, who are seeking to close the gap on the chip giant, which has so far been the central playmaker in the AI revolution.
Virtually unknown to the general public just three years ago, Nvidia now boasts the world’s highest revenues, driven by sales of its graphics cards or graphics processing units (GPUs), the processors that are key to building the technology behind ChatGPT and its rivals.
While Nvidia was not the first to develop GPUs, the California-based company made them its specialty starting in the late 1990s, at the very beginning of cloud computing, and thus has unique experience in the field.
Photo: Bloomberg
Moreover, Nvidia is “a three-headed dragon,” SemiAnalysis founder and CEO Dylan Patel recently said on the No Priors podcast.
The company does not just design chips, but offers an entire infrastructure capable of making them work together with networking and software — the dragon’s two other heads.
Nvidia can “satisfy every level of need in the data center with world-class product,” Jon Peddie Research founder and president Jon Peddie said.
At a considerable distance from Nvidia, whose market share is estimated at about 80 percent depending on the source, Advanced Micro Devices Inc (AMD) has until recently been considered the runner-up.
However, AMD generates the bulk of its revenue from central processing units (CPUs) — processors used for personal and business computers that are less powerful than GPUs — and “can’t divert resources from that golden egg,” Peddie said.
Determined to reduce their dependence on Nvidia, major cloud providers have developed their own processors.
Google began using its Tensor processing unit a decade ago, while Amazon Web Services’ Trainium appeared in 2020.
Today, Google and Amazon account for more than 10 percent of the market and have even overtaken AMD in terms of “performance, pricing, usability, reliability and ability to produce enough chips to satisfy the biggest customers,” SemiAnalysis researcher Jordan Nanos said.
Google is even offering its chips to third-party customers, according to several media reports.
However, Amazon does not sell its Trainium to other players.
The only nation rivaling the US in the sector, China, is seeking to make up for lost time — and is having to do so without the most advanced US chips, which are now subject to export restrictions.
For Nanos, Huawei Technologies Co (華為) ranks among Nvidia’s most credible competitors, alongside Google or Amazon, and ahead of AMD.
Like Google and Amazon, their Chinese equivalents Baidu Inc (百度) and Alibaba Group Holding Ltd (阿里巴巴) are also having their own AI processors manufactured, but these remain merely substitutes for Nvidia’s GPUs.
“They can’t catch up technically for a while using in-country” fabrication facilities, Peddie said.
However, “over time, with its huge and smart workforce, and subsidized investment, China will be able to make state-of-the-art fabrication systems,” Peddie added.
No expert sees the Santa Clara, California, giant loosening its grip on the sector in the near future.
“Nvidia underpins the vast majority of AI applications today,” Gabelli Funds LLC analyst John Belton said. “And despite their lead, they keep their foot on the gas by launching a product every year, a pace that will be difficult for competitors to match.”
Early last month, Nvidia announced that its new generation, Rubin, would be commercialized late next year, with performance for AI functions estimated at 7.5 times that of its flagship product Blackwell.
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