Does AI Kill the $10,000 Camera?

A First-Principles Rethinking of Industrial Camera Features

in the Age of Deep Learning

"I would rather have questions that can’t be answered

than answers that can’t be questioned."

— Richard Feynman

The Provocation

Here’s the uncomfortable question that nobody in the industrial camera industry wants to hear:

Industrial cameras were designed in an era when a human expert looked at the image and made a judgment. The camera had to produce a perfect, calibrated, geometrically correct, high-dynamic-range image because the human visual system was the final inspector. The human needed sharp edges, accurate colors, no distortion, no noise, no motion blur.

But now a convolutional neural network is looking at the image. And a CNN doesn’t see the way humans see. It doesn’t care about “pretty.” It doesn’t need calibrated color. It can learn to see through noise, compensate for distortion, and detect defects in images that would look terrible to a human.

So: how much of that $10,000 camera do we actually still need?