Scientists have developed an algorithm to monitor the underwater chatter of dolphins with the help of machine learning. Using autonomous underwater sensors, researchers working in the Gulf of Mexico spent two years making recordings of dolphin echolocation clicks. The result was a data set of 52 million click noises. To sort through this vast amount of information, the scientists employed an "unsupervised" algorithm that automatically classified the noises into categories. Without being "taught" to recognise patterns that were already known, the algorithm was able to seek original patterns in the data and identify types of click.