We now know that an ANN is created by stacking individual computing units called perceptrons. We have also seen how a perceptron works and have summarized it as Output 1, IF 
.
That is, it either outputs a 1 or a 0 depending on the values of the weight, w, and bias, b.
Let's look at the following diagram to understand why there is a problem with just outputting either a 1 or a 0. The following is a diagram of a simple perceptron with just a single input, x:
For simplicity, let's call , where the following applies:
- w is ...
