Meta-layers

Meta-layers are higher-level structures in machine learning models that oversee and coordinate multiple underlying models or components. Think of them as supervisors that analyze and optimize the performance of several models working together. They help improve accuracy, efficiency, and adaptability by managing how these models interact, share information, or learn from each other. Essentially, meta-layers enable complex systems to be more intelligent and flexible, providing an organized way to enhance overall learning and decision-making processes without directly handling raw data.