Computers Recognizing and Labeling Images

We spent quite a lot of time in the late 90s addressing the labeling of photographs.   So we knew it was hard in general.    Now its become much easier.  Whether it be face recognition in real time, or the ability to label all the common elements in a photo. Not perfectly yet, it can depend on the quality of the image, just like we can be fooled by an image taken in near darkness, or some unusual juxtaposition of things in an image.  But it has become very good.  A high percentage of what we would call 'good' pictures, not meant to fool.   Why?  Good piece below on this and pointer to a paper.   And I can see why we did not figure it out then. We were then pointed in the right direction, but did not emphasize the right elements of learning,  the Data.

How computers got shockingly good at recognizing images
A landmark 2012 paper transformed how software recognizes images. By Timothy B Lee in ArsTechnica  ... "

See the technical 2012 paper.  The date of the emergence of  today's AI.  At the time we were following one of the authors,  Geoffrey Hinton.  Note the use of very large databases, a key element we never fully understood, we had examined similar architectures, but expected them to work with far less data.

And more overview in this book:

How Smart Machines Think   By Sean Gerrish   Foreword by Kevin Scott  MIT Press

Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs. ... "