Describe how you would re-design your neural network architecture to ensure each layer captures a distinct representation of the input data, reducing redundancy and improving overall performance.

To address this issue, I would introduce diversity in the hidden units by using different initialization schemes or activation functions. This would allow each unit to learn a unique function and contribute distinctly to the model’s predictions, reducing feature redundancy and gradient loss during backpropagation.