The following scenario is familiar to most of us, particularly as we grow older:
We walk into a crowded and noisy room full of mostly strangers and unfamiliar heads bobbing up and down. Then off to the side and slightly behind we hear and recognize a familiar voice … we turn our head searching for that old friend we know is there, and after a short search … there she is, head slightly turned away from our view, but recognizable none-the-less. We are surprised and pleased to meet our old friend once more after some number of years and begin renewing the friendship.
The recognition of the voce and face is instinctive and very quick; and we take it for granted with no thoughts of anything unusual other than the mere co-incidence of the meeting.
But behind the scenes in our ears, eyes, nerves and brains is a marvelous and miraculous process called pattern recognition. A pattern recognition that is able to pick out and recognize individual faces and voices out of the billions of faces and voices surrounding us in the world. So let’s take a brief tour of what’s involved in meeting up with our old friend.
The hearing system that most of us have is a partnership between our ears and brain along with the connecting nerves between the two. This stereo audio system is able to sift through the many amplitudes (volumes) presented – the multitudes of widely spread and finely differentiated frequencies – the various timbres presented by the many voices surrounding us in that room full of strangers. And we are able to pick out that distinctive and familiar voice among the multitudes. And by the way, that same set of ears, in the form of the semi-circular canals, is instrumental in our balance system which keeps us from stumbling around in that crowded room.
And the eyes … my gosh what a gift … a gift of obvious design which enables us to stand in awe at the many wonders of our everyday world.
The eyes, as with the ears, are continually involved in a massive process of pattern recognition that allow us to function smoothly within our very busy, active and dangerous world. Eyes that are quick to warn us of the dangers of that car moving too close to us on the freeway. Eyes that quickly recognize that old friend even in a crowded and busy room.
In our modern technological world we have analogies to that busy room. Our Navy ships scan the depths of the ocean with sonar. The pulses transmitted from the sonar antenna bounce off; the ocean floor, schools of fish and even the surface of the ocean, returning a bewildering stream of noise that the computers of the sonar must sift through, filter and cluster to present the operators and commanders an array of potential hazards and threats to the fleet. These sophisticated sonar system require sophisticated computational systems and large amounts of memory storage to accomplish the task in real-time. But most fundamentally they require intelligent designers to create the systems required.
Pattern recognition in the visual world is no less wondrous. When you take a picture of that group at a reunion with a modern state of the art camera, have you noticed the little boxes surrounding the faces? Somehow some very smart scientists and engineers have figured out how to program a computer in your camera to recognize that human faces are part of the picture and visually highlight them for you. And after you take them you can ‘tag’ the individual faces with names in programs like Facebook. Again, sophisticated computational power and large amounts of memory storage are required for the job. And, as in the case of sonar processing, intelligent designers are necessary to create the systems required.
Pattern recognition is not a trivial task in the engineering world. A snippet taken from a Wikipedia article on “pattern recognition” reads thus:
For a probabilistic pattern recognizer, the problem is instead to estimate the probability of each possible output label given a particular input instance, i.e., to estimate a function of the form
where the feature vector input is , and the function f is typically parameterized by some parameters . In a discriminative approach to the problem, f is estimated directly. In a generative approach, however, the inverse probability is instead estimated and combined with the prior probability
using Bayes’ rule, as follows:
So I ask you my friends who believe that Darwinian Evolution … a belief in unguided, unintelligent and strictly natural processes; is it reasonable and rational that such a process could guide you to that reunion in a crowded room?
And to those of you who denigrate and insult those of us who believe such natural capabilities are the result of an Intelligent Design (ID), I would ask … which of us is the IDiot?
Don Johnson – December 2013