A bstract We investigate whether artificial intelligence can reproduce and organize known structures of the Standard Model of particle physics using experimental data and with minimal theoretical inputs. By applying unsupervised machine learning techniques — including data dimensionality reduction and clustering algorithms — to intrinsic particle properties and decay modes, we show that key organizational features of particle physics, such as the relative strength of different interactions and t