'Inexact' Chips Save Power By Fudging the Math

Your definition of math is very limited. Descriptive Geometry is math too.

Path finding systems may use imprecise weight function when making decisions - calculating weights is a major burden.

Using cameras involves image analysis. In essence, you're working with what is a bunch of noise, and you analyze it for meaningful data, by averaging over a whole bunch of unreliable samples. If you can do it 15 times faster at cost of introducing 5% more noise in the input stage, you're a happy man.

In essence, if input data is burdened by noise of any kind - and only "pure" data like typed or read from disk isn't, any kind of real world data like sensor readouts, images or audio contains noise, the algorithm must be resistant to said noise, and a little more of it coming from math mistakes can't break it. Only after the algorithm reduces say 1MB of raw pixels into 400 bytes of vectorized obstacles you may want to be more precise.... and even then small skews won't break it completely.

Also, what about genetic algorithms, where "mistakes" are introduced into the data artificially? They are very good at some classes of problems, and unreliable calculations at certain points would probably be advantageous to the final outcome.

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