On August 28, 2026, South Korean brokerage KB Securities said in a report that China’s drive to localize AI accelerators will likely increase, not reduce, demand for Samsung Electronics’ memory chips. Analyst Kim Dong‑Won argued that domestic Chinese AI accelerators are less compute efficient than Nvidia GPUs, so Chinese AI data centers will need more accelerators and more DRAM capacity to handle the same workloads.
This article aggregates reporting from 1 news source. The TL;DR is AI-generated from original reporting. Race to AGI's analysis provides editorial context on implications for AGI development.
This note from KB Securities underscores how AI geopolitics plays out in the supply chain. On paper, China’s push to develop domestic AI accelerators is a threat to Nvidia and its ecosystem. KB’s analyst argues that, for now, those homegrown chips are less efficient, so Chinese AI data centers will need more accelerators and more DRAM per unit of useful compute. That could turn Samsung Electronics, already a major HBM and DRAM supplier, into a key indirect beneficiary of China’s AI industrial policy, even as US export controls target advanced GPUs. ([prod.chosunbiz.com](https://prod.chosunbiz.com/en/en-finance/2026/08/28/2IEYOVRUDVHTTHH47OF4D64BNU/?utm_source=openai))
For AGI timelines, this matters because memory capacity, not just raw FLOPs, is increasingly a bottleneck for long context and agentic workloads. If Chinese data centers overprovision memory to compensate for weaker accelerators, they still end up with a lot of AGI relevant infrastructure, and companies like Samsung gain the revenue needed to fund next generation memory tech. The upshot is that attempts to slow China’s AI progress through chip restrictions may simply reconfigure demand toward other parts of the stack. As long as capital and political will remain, aggregate global compute and memory for large models will keep rising.



