SK海力士成立风险投资部门拓展AI业务

The talks show that LLM serving bottlenecks sit as much in memory architecture — CXL pooling, HBM bandwidth — as in GPU compute, a framing many benchmark writeups skip. Engineers building inference infrastructure can study the roofline analysis and LMCache MP Mode patterns for their own deployments. The event also signals a growing Korean accelerator and serving stack around FuriosaAI's RNGD and SK hynix memory.

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The roadmap shows memory, not compute, is becoming the binding constraint as AI context lengths grow 30x a year — Micron's bet on 3D DRAM against SK hynix and Samsung's 4F² path will shape GPU pricing for years. Hardware planners, AI infrastructure buyers and investors tracking Nvidia's ecosystem should study the HBM4 and vertical-HBM timelines. The SSD controller gains also offer a concrete benchmark of what AI agents deliver in chip engineering today.

rohanpaul_ai@rohanpaul_aiSource