
AI and Unreliable Electronics (*batteries not included) - spenrose
https://petewarden.com/2016/12/29/ai-and-unreliable-electronics-batteries-not-included/
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spenrose
"our only hope for long-lived smart sensors is driving down the energy used by
local compute to the point at which harvesting gives enough power to run
useful applications. The good news is that existing hardware like DSPs can
perform a multiply-add for just low double-digit picojoules, and can access
local SRAM to avoid the costs of DRAM. If you do the back of the envelope
calculations, a small image network like Inception V1 takes about 1.5 billion
multiply-adds, so 20 picojoules * 1.5 billion gives a rough energy cost of 30
millijoules per prediction (or 30 milliwatts at 1 prediction per second). This
is already an order of magnitude less energy than the equivalent work done on
a general-purpose CPU, so it’s a good proof that it’s possible to dramatically
reduce computational costs, even though it’s still too high for energy
harvesting to work."

