Move AI workloads out of the cloud to reduce power consumption

arm holdings CEO Rene Haas told CNBC’s Jim Cramer on Wednesday that offloading some AI functions could help reduce energy usage.

He suggested that over time, many multi-gigawatt data centers will become unsustainable.

“Look at yourself. So what needs to happen? I think there are two vectors to that,” Haas said. “One is low power, the lowest power solutions available in the cloud. Arm is a big contributor to that. But I think more specifically, it’s about moving AI workloads from the cloud to local applications.”

He said that while AI training will likely always take place in the cloud, the execution of the AI, called inference, could happen locally, on chips in people’s phones, computers and glasses. Haas said history shows that “we’re always going to move to a hybrid model of computing.”

He suggested that there will be hybrid power when it comes to AI, which will help alleviate huge power investments.

Chip designer Arm’s technology powers devices made by many leading Big Tech companies, including: microsoft and Amazon. Major semiconductor company Nvidia is a major shareholder in Arm and actually tried to acquire the company in 2020.

arms and meta The company announced Wednesday that it is expanding its partnership to “extend AI efficiency across all layers of computing, spanning AI software and data center infrastructure,” according to a press release. Arm shares rose on the announcement, ending the day up 1.49%.

Haas told Kramer that the partnership with Meta is “primarily centered around the data center, but more broadly… around software and the associated software stack.” He also touched on Arm’s involvement in Meta’s new Ray-Ban Wayfarer glasses, noting that the technology’s AI runs both in the cloud and locally.

“For example, when you say to your glasses, ‘Hey, Meta,’ it’s not happening in the cloud, it’s actually happening in your glasses, and it’s running on Arm,” Haas said.

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Disclaimer CNBC Investing Club Charitable Trust owns shares in Meta, Microsoft, Amazon, and Nvidia.