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The twin infrastructure impacts of generative AI and how to deal with them

Published by Iron Mountain

Generative AI is transforming data center infrastructure, creating unprecedented power demands and sustainability challenges. AI models, particularly Large Language Models (LLMs), require 10-15 times more energy than traditional CPUs, pushing data centers to adopt high-density power solutions and advanced cooling systems. The rapid growth of AI is also accelerating e-waste, with AI-driven server refresh rates increasing, requiring IT asset lifecycle management, recycling, and remarketing strategies. Iron Mountain Data Centers emphasizes renewable energy, carbon-free power sourcing, and AI-ready infrastructure designs to address these twin challenges, ensuring scalability, efficiency, and long-term environmental sustainability.

 

 

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Related Categories Artificial Intelligence (AI), Artificial Intelligence, Generative AI, Deep Learning, Cognitive Computing, NLP, AI in Business, AI in Healthcare, Metaverse, Sustainable Technology, Augmented Reality, Hyper-Personalisation, Phygital Convergence

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