Question$)$ Let your input space be the set of all vectors consisting of $0$s and $1$s$.$ Suppose you want to make a neural network that detects the pattern $010$ in adjacent components of the vector. Describe a simple convolutional neural network that does this for any size input.

What are the advantages of approach rather than a $$plain$$ neural network. Also consider training from data in your answer.