Why Machine Learning Models Need to Be Updated Regularly

The neural net then takes its guess and compares it to a ground truth about the data, effectively asking an expert, did i get this right? The resulting model is capable of solving complex tasks such as recognizing objects it's never seen before. Neral networks differ from other types of machine learning algorithms in that they have low explainability. They can generate a prediction, but it is very difficult to understand or explain how it arrived at its prediction. Machine learning models get stale. Their real world performance generally degrades overtime if they are not up dated regularly with new training data that matches the changing state of the world.