Intuition about SVD?

I am trying to understand SVD:

A = USV\^t

Matrix U - Eigen vectors of A\^tA matrix

Matrix S - Diagonal singular values

Matrix V - Eigen vectors of AA\^t matrix

What information does A\^tA and AA\^t matrix contain and why eigen vectors are used as basis for transformation?

datascience intuition svd