Deep learning lacks a solid theoretical foundation, relying instead on empirical results and high-level narratives that often fall short. Generalization remains a complex challenge, with powerful models requiring vast amounts of data. Despite these limitations, the ability of deep learning to generalize across various tasks, particularly in computer vision, is seen as a significant advantage.
