Example Concept: AI video upscaling often uses super-resolution techniques, which involve training deep neural networks on high-resolution video data to predict and enhance the details of lower-resolution inputs. By leveraging convolutional neural networks (CNNs) or generative adversarial networks (GANs), these models can intelligently fill in missing details and sharpen edges, resulting in a higher resolution output that maintains the original video's quality.