The relationship between convolution & self-attention

This video explains how self-attention mechanisms in Transformer-based models have replaced Convolutional Neural Networks (CNN) in computer vision, allowing for non-local interactions between pixels. It highlights the differences between convolution and self-attention, including the local receptive field of convolutional layers and the ability of self-attention to look at any pixel in the image in a single step.