by CALEB GARLING
Images like these were created to trick machine learning algorithms. The software sees each pattern as one of the digits 1 to 5.
Humans and software see some images differently, pointing out shortcomings of recent breakthroughs in machine learning.
A technique called deep learning has enabled Google and other companies to make breakthroughs in getting computers to understand the content of photos. Now researchers at Cornell University and the University of Wyoming have shown how to make images that fool such software into seeing things that aren’t there.
The researchers can create images that appear to a human as scrambled nonsense or simple geometric patterns, but are identified by the software as an everyday object such as a school bus. The trick images offer new insight into the differences between how real brains and the simple simulated neurons used in deep learning process images.
MIT Technology Review for more