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Equation 4 · Part 5 · Edge AI Electronics and Sensor Systems in 2035: Scenarios, Signals, and Falsifiable Predictions

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

Approximately equal to; the equality is not exact.

Its job in the formula

Approximately equal to; the equality is not exact.

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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Sources cited in the surrounding passage

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