Computers and machines can see through cameras, but they hardly perceive their visual environment. So they are more or less blind (and even deaf). ExB uses autonomous deep learning algorithms to identify objects and structures in pictures so that computers can learn to see. What seems to be easy for humans is a hard task for AIs.
How deep learning works
Deep Learning is based on artificial neural networks, which roughly mimic the human brain through the simulation of a tightly woven network of simple neurons. These neurons are divided in multiple levels. In a picture recognition task for example the first units register only brightness values of pixels. The next level would recognize that some pixels are connected and represent edges. Subsequent levels decide between horizontal and vertical lines and so on until the neurons could identify an object.
What a seeing computer can be used for
Object recognition is important for machines like autonomous cars, they have to recognize lane markings, traffic signs and other obstacles in their way. But computer vision can also be used for other tasks, for example face recognition (finding, marking and tagging), abnormalities in tissues or finding logos in social media.