Complex models typically outperform simple models on the training set. However, simple models typically outperform complex models on the test set (which is more important).
Simplicity has been beating complexity for a long time. In fact, the preference for simplicity dates back to ancient Greece. Centuries later, a fourteenth-century friar named William of Occam formalized the preference for simplicity in a philosophy known as [[Occam’s razor]]. This philosophy remains an essential underlying principle of many sciences, including machine learning.