The text discusses the use of unsupervised clustering in computer vision datasets, specifically through the FiftyOne Plugin called Interactive Clustering. It explains how clustering can be used to group similar samples together based on certain features or characteristics, and how it can help pre-label datasets, understand data landscape and density, and support baseline assumptions. The text also provides installation instructions for the plugin and demonstrates its use with examples from the KITTI dataset and MNIST dataset. It emphasizes the importance of being familiar with one's data when using clustering algorithms and suggests that users should always double-check results after automated labeling flows.