A canonical problem in computer science is to find the shortest route to every point in a network. A new approach beats the classic algorithm taught in textbooks.

John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning.

That practice is called “human-in-the-loop” computing. Here’s how it works: First, a machine learning model takes a first pass on the data, or every video, image or document that needs labeling.

A similar algorithm, called clustering, is important in unsupervised machine learning. Problem-solving, as with data science, is arguably one of the most important skills in machine learning too.