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  1. 81

    Agentic AI may extend the memory cycle and widen NVDA’s systems edge

    748 wordsEquityX ↗
    • Long-running, token-heavy agentic workloads could make memory the market’s biggest blind spot: long decode raises capacity and bandwidth needs while compression and quantization lose effectiveness.
    • Author favors HBM/DRAM names including MU and SKHY, plus Samsung; current low-to-mid-single-digit P/Es look dislocated if demand outruns supply, sustaining pricing, margins, earnings, and NAND spillover.
    • Historical supply-cycle analysis is a counterweight, but the author expects this cycle’s demand growth to exceed forecast supply growth for longer.
    • NVDA’s integrated compute, networking, interconnect, rack architecture, and software may deliver superior full-system goodput as prefill/decode complexity makes isolated chip benchmarks less relevant; the author remains bullish.