What is the state of AI in computer vision?

If you clicked on this article, you are certainly interested in computer vision applications like image classification, image segmentation, object detection, and more complex tasks like face recognition, image generation, or even style transfer application. As you may already know, with the growing power of our computers, most of these applications are now being realized using similar deep neural networks, what we often refer to as "artificial intelligence models". There are some differences between the deep nets used in these different vision applications, but as of now, they use the same basis of convolutions introduced in 1989 by Yann LeCun. The major difference is our computation power coming from the recent advancements of GPUs. To quickly go over the architecture, as the name says, convolution is a process where an original image, or video frame, which is our input in a computer vision application, is convolved using filters that detect important small features of an image such as edges.