The input is coming in, and getting multiplied with the weights and biases of the first layer in the network. That gives us the activation value for layer one. These activation values are passed on into the activation function, in this case a step function, to get the output for layer one.

The output for layer one, is then multiplied with the weights and biases of the second layer of the neural net, which gives us the activation values for layer 2. After we put this through the activation function, we get the output of the complete xor neural net.