$$C_{\text{edge}}(t) \approx P_{\text{budget}} \cdot \eta(t)$$

Equation 4 · Edge AI & Electronics

Edge AI Electronics and Sensor Systems in 2035: Scenarios, Signals, and Falsifiable Predictions

This equation gives an approximation: it relates the quantities while allowing an approximation.

That structural fact can be written compactly. If $P_{\text{budget}}$ is the (roughly fixed, application-set) power envelope in watts and $\eta(t)$ 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 $C_{\text{edge}}(t) \approx P_{\text{budget}} \cdot \eta(t)$. 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 $P_{\text{budget}}$ 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 $\eta(t)$ — from…

Meanings in this article

• $t$: the time or time index used in this relationship.
• $P_{\text{budget}}$: the because.
• $\eta$: the achieved energy efficiency of the best available accelerator at time t , measured in tera-operations per second per watt.

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