Clustering Without Amnesia: Why Abstraction Keeps Fighting Representation
Opening — Why this matters now We are drowning in data that knows too much. Images with millions of pixels, embeddings with thousands of dimensions, logs that remember every trivial detail. And yet, when we ask machines to group things meaningfully—to abstract—we often get either chaos or collapse. Clustering, the supposedly humble unsupervised task, has quietly become one of the most conceptually demanding problems in modern machine learning. ...