$NVIDIA(NVDA)$ Highlighting inference software as a structural driver is important because it shifts the narrative from “one-time hardware capex” to “ongoing efficiency compounding.”
If token costs keep dropping after deployment, then the same Blackwell GPUs effectively become more valuable over time, not less. That changes the ROI curve for hyperscalers.
The mention of rapid optimization gains (like multi-fold performance improvements in models such as DeepSeek V4 within a short window) reinforces the idea that software-level improvements are now a major lever in AI infrastructure economics.
NVIDIA working across inference stacks (including integrations with tools like Cursor AI) further supports the view that this is not just hardware dominance, but a full-stack optimization cycle.
In simple terms: hardware builds the base, but software keeps extending the lifespan and profitability of that hardware.
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