From Model-centric to Data-centric Artificial Intelligence

Two basic components of all AI systems are Data and Model, both go hand in hand in producing desired results. In this article we talk about how the AI community has been biased towards putting more effort in the model, and see how it is not always the best approach. We all know that machine learning is an iterative process, because machine learning is largely an empirical science. You do not jump to the final solution by thinking about the problem, because you can no easily articulate what the solution should look like. Hence you empirically move towards better solutions.