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The article addresses the fundamental bottleneck of AI inferencing scalability, arguing that physical data center expansion is insufficient to solve compute scarcity without addressing underlying software engineering and architectural constraints. This analysis directly impacts the strategic planning for AI infrastructure and resource allocation within the machine learning ecosystem.
AI’s Compute Scarcity Problem Will Not Be Solved by Data Centers Alone
For the past couple years, companies have been treating the high demand and explosive growth for AI inferencing as a construction project rather than a software engineering problem. Their answer has been to purchase as many GPUs as possible, build more data centers, and acquire as much power as possible. However, construction scales linearly, not […] The post AI’s Compute Scarcity Problem Will Not Be Solved by Data Centers Alone appeared first on HPCwire.
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