First, run a gradient descent to find such that . This is called "projecting an image back to style latent space". Then, can be fed to the lower style blocks, and to the higher style blocks, to generate a composite image that has the large-scale style of , and the fine-detail style of . Multiple images can also be composed this way. StyleGAN-2 StyleGAN-2 improves upon StyleGAN-1, by using the style latent vector to transform the convolution layer's weights instead, thus solving the "blob" problem. This was updated by the StyleGAN-2-ADA ("ADA" stands for "adaptive"), which uses invertible data augmentation as described above. It also tunes the amount of data augmentation applied by starting at zero, and gradually increasing it until an "overfitting heuristic" reaches a target level, thus the name "adaptive". StyleGAN-3 StyleGAN-3 improves upon StyleGAN-2 by solving the "texture sticking" problem, which can be seen in the official videos. They analyzed the problem by the Nyquist–Shannon sampling theorem, and argued that the layers in the generator learned to exploit the high-frequency signal in the pixels they operate upon. To solve this, they proposed imposing strict lowpass filters between each generator's layers, so that the generator is forced to operate on the pixels in a way faithful to the continuous signals they represent, rather than operate on them as merely discrete signals. They further imposed rotational and translational invariance by using more signal filters. The resulting StyleGAN-3 is able to solve the texture sticking problem, as well as generating images that rotate and translate smoothly. Applications GAN applications have increased rapidly. Fashion, art and advertising GANs can be used to generate art; The Verge wrote in March 2019 that "The images created by GANs have become the defining look of contemporary AI art." GANs can also be used to inpaint photographs or create photos of imaginary fashion models, with no need to hire a model, photographer or makeup artist, or pay for a studio and transportation. GANs have also been used for virtual shadow generation. Interactive Media In 2020, Artbreeder was used to create the main antagonist in the sequel to the psychological web horror series Ben Drowned. The author would later go on to praise GAN applications for their ability to help generate assets for independent artists who are short on budget and manpower. Science GANs can improve astronomical images and simulate gravitational lensing for dark matter research.