Memory must adopt foundry model to fix AI inference bottleneck, says Korean scholar

The memory industry faces a structural inflection point: AI inference’s extreme demands for bandwidth and power efficiency are forcing DRAM and HBM to shift from commoditized products to customized solutions. This triggers a technical cascade—TSMC’s CoWoS capacity constraints are accelerating SK Hynix and Samsung’s development of client-specific memory interface protocols, compelling EDA toolchains, test equipment, and interposer designs to be rearchitected. On compliance, tightening U.S.-EU export controls on advanced packaging materials increase supply chain fragility under a foundry model, especially for photoresists and ultra-pure gases. Micron has quietly launched a 'Design-in Foundry' pilot, while CXMT may leverage localized support to penetrate China’s AI chip clients. Within 18 months, memory foundry won’t replace IDM dominance but will become a gatekeeper for high-end markets—vendors lacking co-definition capabilities will be excluded from AI supply chains.