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Beyond Raw Power: Big Tech CSPs Pivot to Liquid-Cooled Racks to Break the 'Memory Wall'
Electronic Technology · Semiconductors · economic_daily · 2026-10-24
Major cloud providers are shifting to high-density, liquid-cooled rack systems to overcome memory bandwidth constraints and thermal limits in the AI era.
What Happened
Strategic Pivot by Cloud Giants: Google, Microsoft, Amazon, and Meta are shifting their data center focus from raw compute power to overcoming the 'memory wall.' As AI transitions into an inference-heavy commercial phase, these companies are leveraging custom ASICs and high-capacity HBM to maximize token output per watt.
Architectural Revolution: To handle complex models and long-context inference, CSPs are abandoning traditional server form factors in favor of fully liquid-cooled rack-scale systems. This 'scale-up' architecture allows dozens or even hundreds of chips to share memory, effectively functioning as a single massive processor to meet the physical demands of modern AI workloads.
Inference-Centric Design: With over 70% of cloud data center power now dedicated to inference, major providers are designing chips specifically for this purpose. New hardware, such as Microsoft's Maia 300 and Google's TPU v7, is optimized to handle agentic AI and real-time multimodal interactions more efficiently than general-purpose GPUs.
Impact on Supply Chains: The industry-wide transition to advanced manufacturing processes and HBM4 technology is reshaping the global semiconductor and server supply chain. Taiwan's ecosystem, spanning IP, foundry services, advanced packaging, and liquid cooling assembly, is positioned to capture significant value from this infrastructure transformation.