Cortica teaches autonomous vehicles with unsupervised learning

The key, according to the company, is in the use of unsupervised learning that allows an autonomous system to process data and figure out its environment. For example, you could feed the system a thousand images of stop signs -- some faded, some obscured by tree branches, etc. Stop signs, for example, are red with white borders and eight sides. The AI can learn as it goes that sometimes that red is faded and sometimes a white border will be obscured by a tree branch, but it can make changes as needed to classify stop signs as stop signs.