Learning to Optimize (L2O) seeks to replace traditional hand-designed optimizers, such as SGD and Adam, with learned optimization strategies using deep learning. Just as deep learning replaced handcrafted feature extractors in computer vision, L2O aims to replace manual optimizer design with learned models that generalize across tasks.