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The Power Paradox: How Big Tech is Turning to Nuclear and Advanced Clean Energy to Fuel the AI Revolution

Artificial intelligence is undergoing the most rapid infrastructure scale-up in human history. As tech giants deploy hundreds of thousands of high-performance GPUs to train next-generation Large Language Models (LLMs) and power real-time AI agents, they have stumbled upon an unyielding physical reality: the global energy grid is running out of headroom. A single AI-generated query consumes anywhere from 3 to 10 times more electricity than a traditional Google search. Training a single frontier AI model can draw as much electricity as a small town uses in a year. As hyperscalers—including Microsoft, Google (Alphabet), Amazon (AWS), and Meta—invest upwards of $200 billion annually into AI data center infrastructure, they face a dual dilemma: Uninterrupted Power Needs: AI workloads require 24/7/365 continuous, heavy load capacity. Decarbonization Commitments: Corporate climate goals mandate 100% zero-carbon energy sources. Intermittent renewables like traditional solar and wind, while ...
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