Let's consider how a human brain learns in order to see the ways in which a neural network is similar and the ways in which it is different.
Our brain contains a large number of neurons, and each neuron is connected to thousands of nearby neurons. As these neurons receive signals, they fire if the input contains a certain amount of a given color or a certain amount of a given texture. After millions of these interconnected neurons fire, the brain interprets the incoming signal as a certain class.
Of course, these connections are not set permanently but rather change dynamically as we continue to have experiences, notice patterns, and discover relationships. If we try a new fruit for the first time and discover that it is really sour, then all the attributes that help us recognize this fruit are connected with things that we know...
