"The code reflects AI model or algorithm which is trained using the data. The conventional model-centric AI focuses on improving code to achieve better results given a fixed set of data. AI developers generally consider the training datasets from which their code is learning as a collection of ground-truth labels, and their AI model is made to fit that labeled training data. Thus, this approach generally assumes the training data as external from the AI development process."