彼时，新兴技术正从边缘切入，重构存储生态。比如MRAM（磁阻存储器）兼具SRAM速度、DRAM密度与Flash非易失性，已在车规级MCU、工业控制器中商用，三星、台积电、英特尔等均在持续推进该技术进展。ReRAM（阻变存储器）单元面积小，读写速度是NAND的1000倍，同时功耗可以降低15倍。CXL（Compute Express Link）虽非存储介质，却是内存池化的关键。通过CXL，服务器可将多个DRAM/HBM模块虚拟为统一内存池，大幅提升AI训练效率。Intel、AMD、三星正推动其成为下一代数据中心标配。不过，新兴存储并非要“取代”DRAM或NAND，而是填补其无法覆盖的“价值缝隙”。未来将是“传统+新兴”的分层共存格局。
But those tricks, I believe, are quite clear to everybody that has worked extensively with automatic programming in the latest months. To think in terms of “what a human would need” is often the best bet, plus a few LLMs specific things, like the forgetting issue after context compaction, the continuous ability to verify it is on the right track, and so forth.
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