The post discusses the CosAE method, which utilizes learnable Fourier series techniques for improving image restoration tasks, particularly focused on achieving super-resolution. The results highlight an impressive inference time of just 36 milliseconds for achieving 4X super resolution on a V100 GPU, showcasing both efficiency and effectiveness. However, a notable concern expressed in the comments is the absence of released code, which can limit accessibility and further exploration by the community. The advancements in this method suggest potential opportunities for enhancing image quality significantly within various applications. Overall, this development represents a meaningful step forward in the intersection of AI and imaging technology, though access to the underlying code may hinder broader adoption and experimentation.