US lawmakers will be urged by Microsoft and other AI leaders to open additional government data sets for AI training and expedite federal permitting for AI energy demands.
Sam Altman, the CEO of OpenAI, will inform lawmakers that as AI systems advance, people will want to use them more, and that in order to meet this demand, more chips, training data, electricity, and supercomputers will be needed. "We want to build a brain for the world and make it super easy for people to use it, with common-sense restrictions to prevent harm," Altman stated in his testimony.
The energy intensity of AI compute is highlighted in CoreWeave CEO Michael Intrator's written testimony, which cites an Energy Department projection that data centers' electricity consumption might increase from 4.4 percent in 2023 to 12 percent in 2028.
"Millions of hours of training, billions of inference queries, trillions of model parameters, and continuous dynamic scaling are all driving an insatiable hunger for compute and energy that borders on exponential," he said.
He called for efforts "to streamline the permitting process to enable the addition of new sources of generation and the transmission infrastructure to deliver it."
Leading in AI, according to AMD CEO Lisa Su, necessitates "rapidly building data centers at scale and powering them with reliable, affordable, and clean energy sources."
She added "moving faster also means moving AI beyond the cloud. To ensure every American benefits, AI must be built into the devices we use every day and made as accessible and dependable as electricity."
Citing China's and the UK's moves, Smith demanded that U.S. government data sets be made available for AI training.
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"The federal government remains one of the largest untapped sources of high-quality and high-volume data," Smith said. "By making government data readily available for AI training, the United States can significantly accelerate the advancement of AI capabilities."