Schneider Electric Calls for Scalable, AI-Ready Data Centers Infrastructure as Nigeria Enters a New Era of Intelligent Computing
AI is driving one of the most significant shifts the...
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Schneider Electric has released new insights on how the rapid adoption of artificial intelligence is transforming data centers requirements across Nigeria, urging operators, policymakers, and enterprises to redesign infrastructure for higher density, improved efficiency, and stronger resilience. With generative AI tools becoming mainstream across banking, telecoms, healthcare, manufacturing, and government, the company warns that traditional facilities are not equipped to meet the emerging demands of AI training and inferencing.<br />
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AI is driving one of the most significant shifts the global IT industry has ever seen. Large models require enormous computational power, pushing energy consumption and thermal loads far beyond conventional norms. Yet while global conversations often focus on the intensive process of AI model training, the true business value will be unlocked through inferencing, the stage where AI makes predictions or decisions in real time.<br />
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Training vs. Inferencing: Why the Distinction Matters for Nigeria<br />
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Schneider Electric highlights that the two AI workloads have vastly different implications for infrastructure:<br />
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AI training involves teaching models with massive datasets, requiring racks of GPU servers operating as unified clusters that often exceed 100 kW per rack. This places extreme pressure on power, cooling, and electrical architecture. Liquid cooling methods such as direct-to-chip and rear-door heat exchangers are no longer optional but essential.<br />
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AI inferencing, on the other hand, is where AI is deployed across real-world applications — from fraud detection in banking to diagnostics in healthcare or real-time analytics in retail and logistics. While traditionally less energy-intensive than training, inferencing workloads in Nigeria are growing more complex, with some advanced workloads reaching 40–80 kW per rack.<br />
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Because inferencing is deployed everywhere, in the public cloud, colocation facilities, corporate data centers, and increasingly at the edge, Schneider Electric...
