Nvidia Reportedly Weighing Investment in Musk’s xAI

Nvidia is in discussions to invest in Elon Musk’s artificial intelligence (AI) startup, according to published reports.

Musk’s AI firm xAI is hoping to raise several billion dollars, valuing the company at around $40 billion, the New York Post reported Friday (Nov. 1).

A separate report by The Information says Musk had been in discussions with tech companies and venture firms such as Sequoia Capital, Andreessen Horowitz and Vy Capital.

Musk is expecting in January to hold a major funding round that could value xAI at as high as $75 billion, two sources told the Post.

And an analyst for Nvidia, speaking with the newspaper on the condition of anonymity, said that xAI’s rivals would still buy chips from Nvidia even if it invests in Musk’s company.

“If not, this transaction would never go forward,” the analyst said.

PYMNTS has contacted Nvidia for comment but has not yet gotten a reply.

During a Series B round in May, xAi raised $6 billion, gaining a pre-money valuation of $18 billion. The company said at the time that the new funds would help it take its first products to market, develop advanced infrastructure and accelerate its research and development.

And in September, the company introduced its Colossus 100k H100 training cluster. Writing about it on X, Musk called it “the most powerful AI training system in the world. Moreover, it will double in size to 200k (50k H200x) in a few months.”

In other AI news, PYMNTS wrote last week about a MIT spinoff Liquid AI’s creation of systems that can match current capabilities while using fewer neurons, a development that could potentially reduce the massive computing costs that have kept many businesses from investing in AI.

Liquid AI’s “liquid neural networks” require only dozens of neurons to guide drones and vehicles — rather than the millions required for conventional AI systems. The technology could forge a path to reducing the computing power and energy costs that have kept some businesses from fully embracing AI technology.

“It could democratize AI adoption by making AI technologies more accessible and affordable to businesses across various industries,” Jesal Gadhia, head of engineering at AI company Thoughtful, told PYMNTS. 

“This affordability would enable even smaller companies to implement AI solutions, leading to widespread innovation, increased efficiency, and reduced energy consumption throughout different sectors. This mirrors the transition we experienced with computing: initially, only select organizations could build and operate mainframes, but now computing is ubiquitous — from our watches to our cars.”

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