The executive confirmed the chipmaker’s participation in xAI’s latest funding round in an interview with CNBC Wednesday (Oct. 8).
An earlier report by Bloomberg News said that Musk’s artificial intelligence (AI) startup is aiming to raise about $20 billion, with sources familiar with the matter telling the news outlet that Nvidia would contribute $2 billion.
Huang told CNBC he’s “super excited” about the funding opportunity, adding that he wishes he could give the billionaire more money.
“Almost everything that Elon is part of, you really want to be part of as well,” Huang said.
The report notes that Nvidia has also invested in AI data center operator CoreWeave, which Huang said he views as one of several “terrific investments” made by his company recently.
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“[They’re] really special companies, and they’re building, they’re part of our ecosystem building out the AI infrastructure for the world,” the CEO said.
Huang also said he’s surprised Advanced Micro Devices (AMD) offered 10% of itself to OpenAI as part of a multibillion-dollar pact announced this week.
“It’s imaginative, it’s unique and surprising, considering they were so excited about their next generation product,” he told “CNBC’s Squawk Box.”
“I’m surprised that they would give away 10% of the company before they even built it. And so anyhow, it’s clever, I guess.”
Nvidia itself has pledged a record $100 billion to OpenAI, an investment CNBC noted that highlighted concerns about the “circular nature” of some AI infrastructure agreements.
Asked how OpenAI will pay for its end of the deal with Nvidia, Huang said, “They don’t have the money yet.”
“They’re going to have to raise that money through, first of all, their revenues, which is growing exponentially, equity or debt,” he added. “They gave us the opportunity to invest alongside other investors when the time comes.”
In related news, PYMNTS wrote earlier this week about AI’s maturation into enterprise infrastructure in the wake of recent infrastructure announcements from Nvidia and others, and this trends consequences for the world of payments and finance.
“As institutions scale agentic decision systems, every layer from fraud detection to credit scoring now depends on intelligence that is explainable, stable, and auditable,” PYMNTS wrote. “Deploying AI at scale is also proving costly.”
As reported here recently, for every dollar spent on AI models, businesses often shell out five to 10 times more on integration, compliance, infrastructure and monitoring to ensure their systems are production ready.
Source: https://www.pymnts.com/