We might be inclined to now think that setting all our weights to zero will achieve maximum symmetry. However, this is actually a very bad idea, and our model will never learn anything. This is because when you do a forward pass, every neuron will produce the same result; so, during the backpropagation step, all the weights will update in the same way. This means the model can never learn an informative set of features, so don’t initialize like this.