Data Centric AI Vs. Model Centric AI: How to take maximum advantage of both.

Data-centric AI: The term "data-centric AI" refers to the use of machine learning techniques and algorithms that are optimized for specific kinds of data. This approach is particularly effective in domains where there is a shortage of representative and labelled datasets. Industries such as healthcare, manufacturing, and agriculture often have large volumes of unlabeled data and require an AI model to be trained from these sources. A data-centric approach emphasizes the technical aspects of a task instead of focusing on the algorithm itself. To demonstrate how useful, such an approach is, Andrew Ng and his team organized a competition called the Data-Centric AI Competition.