Elon Musk isn’t stopping at acquiring 1 million Nvidia GPUs for AI training. The billionaire wants millions more as his startup xAI races to beat the competition on next-generation AI systems.
Musk today tweeted that xAI aims for compute power that’s on par with 50 million Nvidia H100 GPUs, the enterprise-grade graphics chip widely used for AI training and running chatbots. “The xAI goal is 50 million in units of H100 equivalent-AI compute (but much better power-efficiency) online within 5 years,” he said.
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Musk’s tweet comes a day after rival Sam Altman, the CEO of OpenAI, wrote in his own post about plans to run “well over 1 million GPUs by the end of this year,” with the goal of exponentially scaling up the compute power by “100x.” Meta CEO Mark Zuckerberg, meanwhile, has a similar goal; he wants mega data centers devoted to developing AI super intelligence.
These growing AI investments underscore how expensive it is to scale up (and attract top talent). Musk’s tweet doesn’t mean he’ll try to buy 50 million GPUs, though. The H100 was introduced in 2022 before Nvidia began offering more powerful models, including in the GB200, which can reportedly deliver an up to 2.5 times performance boost.
Nvidia has also released a roadmap that outlines two additional GPU architectures, Rubin and Feynman, which promise to unleash more powerful AI chips in the coming years with improved power efficiency. Still, Musk’s xAI will likely need to buy millions of Nvidia GPUs to reach his goal.
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In the meantime, Musk said in another tweet that xAI’s Colossus supercomputer in Memphis, Tennessee, has grown to 230,000 GPUs, including 30,000 Nvidia GB200s. His company is also building a second Colossus data center that’ll host 550,000 GPUs made up of Nvidia’s GB200s and more advanced GB300 chips.
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This compute power requires enormous amounts of electricity; xAI is using gas turbines at the Colossus site, which environmental groups say are worsening the air pollution in Memphis.
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About Michael Kan
Senior Reporter
