AI/ML Data Centers in the Modern Era: Efficiency, Complexity, and the Evolving Role of Compliance in Critical Infrastructure
DOI:
https://doi.org/10.63282/3050-922X.ICRCEDA25-141Keywords:
AI data centers, Machine learning infrastructure, Energy efficiency, Computational complexity, Data center optimization, Edge–cloud continuum, Sustainable computing, Green AI, Regulatory complianceAbstract
The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) technologies into the critical infrastructure is happening at an unprecedented pace. It's changing the functional, structural, and governance aspects of contemporary data centers. There is a rapid evolutionary response, emerging with features like high-density architecture, increased GPU clusters, and advanced cooling systems to AI/ML workloads. Meanwhile, the global compliance with safety, electromagnetic compatibility (EMC), environmental policies, and other considerations becomes increasingly challenging. This study brings to light the strategic importance of compliance engineering in the context of global innovation stasis and infrastructure vulnerability. It also analyzes the operational and regulatory burdens associated with AI/ML data centers and proposes a compliance model that supports flexibility and scalability
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