Recent studies have shown that human languages are optimally balanced between accuracy and complexity, Tech Xplore reports. In a study published in the journal Proceedings of the National Academy of Sciences, researchers formed two artificial neural networks trained with two generic deep learning methods. As researcher Marco Baroni explains: “We made the networks play a colour-naming game in which they had to communicate about colour chips from a continuous colour space. We did not limit the “language” they could use. However, when they learned to play the game successfully, we observed the colour-naming terms these artificial neural networks had developed spontaneously.” The authors found that the emerging colour vocabulary has exactly the same property of optimizing the complexity/accuracy trade-off found in human languages.