The XOR limit of a linear model, such as the original perceptron

A linear model cannot solve the XOR problem expressed as follows in a table:

The following graph shows the linear inseparability of the XOR function represented by one perceptron:

The values of the table represent the Cartesian coordinates in this graph. The circle with a cross at (1,1) and (0,0) cannot be separated from the circles at (1,0) and (0,11). That's a huge problem. It means that Frank Rosenblatt's f(x,w) perceptron cannot separate, and thus not classify, these dots into clouds and trees; an object used to identify that requires linear separability.

Having invented the most powerful concept of the 20th century—a neuron that can learn—Frank Rosenblatt had to bear with this limitation through the 1960s.

Let's vindicate this injustice with a vintage solution.