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Equation 4 · Part 1 · Edge AI Electronics and Sensor Systems in 2035: Scenarios, Signals, and Falsifiable Predictions

Symbol C_edge

Cedge(t)≈Pbudget⋅η(t).C_{\text{edge}}(t) \approx P_{\text{budget}} \cdot \eta(t).
CedgeC_{\text{edge}}

What this part means

CeC_edge is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

Its job in the formula

CeC_edge is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

The passage around this formula

That structural fact can be written compactly. If PbudgetP_{\text{budget}} is the (roughly fixed, application-set) power envelope in watts and η(t)\eta(t) is the achieved energy efficiency of the best available accelerator at time t , measured in tera-operations per second per watt, then the usable on-device compute throughput is approximately Cedge(t)≈Pbudget⋅η(t)C_{\text{edge}}(t) \approx P_{\text{budget}} \cdot \eta(t). This is not a scaling law in the sense of a fitted curve; it is closer to an accounting identity, and its value is in what it rules out. Because PbudgetP_{\text{budget}} is nearly constant for a given device class, essentially all of the growth in on-device model capability that anyone can expect by 2035 has to come from growth in η(t)\eta(t) — from…

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