Sadly, I don't have a publicly available link for this.

But no, this is not AI upscaling.

Instead, it is representing the input image in a feature space trained to store natural images and then reconstructs the output from that intermediary representation. If chosen well, the intermediary will store details relevant for high quality images, but discard those specific to low quality images, like noise.

It's called a convolutional autoencoder with bottleneck.