For example, you might train a deep learning algorithm to recognize cats on a photograph. You would do that by feeding it millions of images that either contains cats or not.

This categorization seems to be rooted in the difference between supervised and unsupervised ... The algorithm will respond by turning ... In one example, an AI program taught itself to play 49 ...

Danny Sullivan, Google's Search Liaison, posted on X explaining the differences between algorithm updates, like core updates, and then data refreshes, the data that goes into those ranking systems.