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AI's $61 Billion Power Play Is Over. The Next Trillion-Dollar Race Is Efficiency.
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AI's $61 Billion Power Play Is Over. The Next Trillion-Dollar Race Is Efficiency.

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As the AI industry's data center spending tops $61 billion, former Facebook exec Chris Kelly says the next race is for efficiency. The companies that solve AI's power and cost problem will emerge as the next winners.

The artificial intelligence boom is entering a new, critical phase where brute force gives way to strategic efficiency, according to former privacy chief . Speaking to CNBC, he argued that the next big winners in AI won't just build bigger models, but will be those who can drastically cut the immense costs and power consumption of training them, a timely warning as the industry's infrastructure spending spree tops this year.

Hyperscalers have poured money into a global data center buildout, with infrastructure dealmaking accumulating over in alone, according to S&P Global. has committed over to AI initiatives in the coming years, including massive partnerships with GPU leader and infrastructure giants and .

But this frenzy is straining an already fragile electric grid. A joint project by and , announced in September, includes at least of data centers. That's roughly equivalent to the annual power consumption of U.S. households, or the entire peak summer demand of New York City in .

believes this challenge is the industry's next great opportunity. "We run our brains on . We don't need gigawatt power centers to reason," he said. "I think that finding efficiency is going to be one of the key things that the big AI players look to."

The pressure to reduce costs is already mounting. In a sign of what's to come, Chinese firm claimed in December to have launched a free, open-source large language model for under — a fraction of the cost for its U.S. competitors.

PRISM Insight: The New AI Winners

For investors, the focus is shifting from companies that simply buy the most GPUs to those that make each compute cycle count. Watch for innovators in efficient chip architecture, advanced cooling systems, and model optimization software. The ability to do more with less power will define the next generation of AI leaders.

본 콘텐츠는 AI가 원문 기사를 기반으로 요약 및 분석한 것입니다. 정확성을 위해 노력하지만 오류가 있을 수 있으며, 원문 확인을 권장합니다.

AIData CentersInvestmentNvidiaEnergyHYPEEfficiency

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