Which of the following is FALSE about PCA and Autoencoders?

Group of answer choices

PCA works well with non$-$linear data while Autoencoders are best suited for linear data

Both PCA and Autoencoders are dimensionality reduction techniques

PCA finds the orthogonal dimensions while Autoencoder doesn't have to$.$

Autoencoder has the advantage of being able to handle large datasets with many features.