What is the gnash cake method?

The Gnash Cake Method is a technique used in machine learning and statistics for optimizing neural networks, particularly in the context of training deep learning models. It focuses on generating a sequence of models that iteratively refine their predictions based on previous outputs, effectively "gnashing" through layers of information to improve accuracy. This method can enhance convergence speed and model performance by leveraging the strengths of previous iterations. It is often applied in scenariOS where traditional optimization methods may struggle.