The latest Nvidia Corp. earnings report crushed Wall Street expectations and gave the company a market capitalization approaching $2 trillion. It was yet another sign that as enterprises attempt to navigate the current tech landscape, the impact of artificial intelligence remains profound.

As the primary beneficiary of significant demand for computing power to drive AI-centric projects, Nvidia has become a bellwether, lifting the stocks of other tech businesses across the globe. Nvidia’s rise to market prominence has paralleled AI’s own explosion and moved the company far beyond its original roots.

“They were just two years ago primarily a gaming and a crypto mining company,” said Dion Hinchcliffe (pictured, second from right), vice president and principal analyst at Constellation Research Inc. “They are first and foremost now an AI company, and they’re selling to businesses. The growth is due to the fact that AI is the future of business. They’ve plugged into that.”

Hinchcliffe spoke with with theCUBE Research executive analyst John Furrier (far left), during a Power Panel CUBE Conversation, from SiliconANGLE Media’s livestreaming studio in Palo Alto. He was joined by Tim Crawford (second from left), chief information officer strategic advisor at AVOA LLC, and David Linthicum (far right), principal analyst at theCUBE Research, and they discussed the factors contributing to Nvidia’s success and market dynamics that could affect future growth.

Sales growth for Nvidia over 400%

Nvidia’s earnings momentum, which included data center GPU sales growth of 409% in the most recent quarter, has been driven by a need for processing power to train AI models and power workloads in production.

“Some of the chipset changes, but then also the applications that are being used by developers to help them build new applications on top of this new methodology are really helping catapult it as well,” Crawford said. “We were kind of tapping out in where we were with regards to traditional processing opportunities, and we needed something different.”

In addition to the processing power provided by its GPUs, Nvidia also brought a proprietary CUDA software solution to the table. CUDA, a parallel computing platform and application programming interface, has appealed to developers seeking to maximize GPU technology.

“It’s a set of APIs and it’s an architecture, and they’ve managed to convince the developer community that’s the best way to develop games and all the other ways to use GPUs,” Hinchcliffe said. “Nvidia really has built this critical mass around the developer community that understands how to use their proprietary APIs to produce the world’s most compelling gaming software and artificial intelligence models. They have built the best-in-class API, which has market dominance right now.”

Edge and cloud could impact future growth

Will that market dominance continue? The ever-shifting dynamics of the tech industry will probably impact Nvidia at some point, according to Linthicum.

“I’m not really as bullish with the fact that everybody is going to move toward Nvidia each and every time,” Linthicum said. “I think ultimately there are going to be other proprietary chips that come into play. Someone always comes up and builds a better mousetrap, and I think that’s where these guys have vulnerability right now.”

One area that could become competitive is in migration of AI processing to the edge. GPUs for AI processing are powerful but expensive, and the economics of smaller device processing could lead to a shift in model size.

“In manufacturing, you’re pulling those models all the way to robots,” Crawford said. “It’s not the really big models that are running on these GPUs; it’s much smaller models. I think the edge-to-cloud dynamic is definitely one piece that will make others shine and give Nvidia a little bit of pressure.”

The analysts also discussed how evolving cloud models could also impact Nvidia’s future prospects. Many organizations aiming to implement AI extensively might find cloud solutions financially prohibitive, leading them to opt for an on-premises setup utilizing a variety of processor types, according to Linthicum.

“We have these micro clouds, which are anything ‘dot AI’ out there, that are providing these GPU systems as a service, and they become a good alternative as well,” he said. “What they are trying to do is basically become a cloud service within your portfolio that just focuses on running AI applications extremely fast.”

In the meantime, Nvidia continues to capitalize on broad-based market demand for its technology. The company’s earnings release indicated that current demand was being driven across multiple industries, including healthcare, financial services and automotive. Nevertheless, competition is coming, and one analyst noted that it would be unrealistic to think that the chipmaker’s startling run of success could continue at its current pace.

“Nvidia’s luck isn’t going to last forever; they’re probably close to their peak of market dominance,” Hinchcliffe said. “But they have the maturity and they have the developers. I think that’s what’s going to carry them along for the next couple of years while the Intels and the AMDs get the maturity in their AI stacks and in their AI chipsets and start really taking on the market.”

Here’s the complete CUBE Conversation:

Photo: SiliconANGLE