No one speaks exactly like you do. Sure, your parents and siblings are close (except your brother Pete, who still calls the morning meal “breakferest”), but the words that enter your ears are never exactly those that come out your mouth. Still, you generally know what people are saying when they wag their pie holes.
This is because your mind is fuzzy.
We don’t need to hear language that precisely matches our expectations. We only need sounds that make our brains’ interpretations very likely. This is fuzzy logic: making judgments that aren’t simply true or false, but are somewhere on the spectrum between the two. Thus when Pete says “breakferest” you know he’s most likely referring to the morning meal.
And your brain does this all the time. Is a room hot or cold? Is that a good pitch to swing at? Is a person short or tall? Are you tired or energized? Are you fashionably or rudely late? Are you sufficiently caffeinated? When is a fellow freeway driver a threat? None of these is an either/or choice—we evaluate them all on gradients—and where they are on these sliding scales affects our behavior. Maybe when a slider hits a certain tipping point, you take an afternoon nap, or swing for the fence, or give that chip-eating, cell-talking, radio-fiddling driver a little extra space.
In addition to creating our basic ability to communicate with other human beings and exist in a messy world, fuzzy logic is useful when cooking rice. To most rice cookers, rice is simply “cooked” or “not.” If “not,” the machine keeps cooking. If “cooked,” it stops. Not so with the Zojirushi NS-ZCC10. Like the human mind, the machine senses gradients—mostly raw, partially cooked, almost there, shit it’s burning, etc.—and adjusts its behavior based on these partial states. For example, a fuzzy logic cooker may sense its rice cooking too quickly on a hot day and turn the heat slightly lower.
And rice cookers aren’t the only application of fuzzy logic outside the brain. Think about your photo-retouching software that’s able to find where a person stops and the background starts. Finding this edge isn’t an all-or-nothing proposition. It’s fuzzy. You go from “definitely person” to “definitely background” but between the two, the software uses fuzzy logic to pick where to draw the actual line. Your e-mail spam filter uses fuzzy logic too: What’s the percentage chance that an e-mail containing the words refinance, national lottery, and pen1s is spam?
Fzzuy Rdaeing
The barin’s fzzuy ligoc alowls you to raed tihs, deipste the jumlbed lteetr odrer. It wuold be mcuh hdraer if the fisrt or lsat ltteers wree mvoed.
Fuzzy logic also makes The Lord of the Rings; WALL-E, I, Robot; Eragon; Flags of Our Fathers; and many other movies possible. Each of these movies contains a massive crowd or battle scene. And in each of these scenes, the fuzzy logic of a simulation software called Massive digitally controls the movements of the people within these crowds. Imagine a human crowd: Each person acts independently, using group cues to guide their own movements. Thus sections of the crowd stop and start at different speeds, edges morph in different directions, and individuals sometimes veer from the group’s exact direction. But the whole creates the effect of a fairly homogenous moving blob. The same is true with Massive—each individual is pushed, pulled, and bounced by others in the group, but the overall crowd moves like a crowd.
Are you too tired to keep reading? Maybe you have time for just one more topic?
It’s fuzzy.