GAN are the days for NVIDIA

NVIDIA's model works better than the rest when it comes to customised prompts, due to the expert denoising system which trains denoisers to maintain fidelity to the textual prompt even in the later stage of the generation process. But, this is not the first time NVIDIA stepped into the waters of text-to-image modelling. Before coming up with eDiffi, NVIDIA used deep learning models to create versions of the GauGAN model. The second version of the model, released in November 2021, was trained on 10 million high-quality landscape images. The application demo allowed users to produce images based on any text input they provide. The GauGAN model is based on generative adversarial networks (GAN), unlike eDiffi, which uses diffusion modelling for generating images. So why did NVIDIA take a departure from using GAN for their text-to-image feature?