Introduction Concepts of correlation and regression may be applied not only to ordinary one-dimensional variates but also to variates of two or more dimensions. This is the first sentence from the paper “Relations Between Two Sets of Variates” ( Hotelling 1936 ) by statistician and economist Harold Hotelling. This paper introduced Canonical Correlation Analysis (CCA). In modern terminology, “CCA is used to find a common signal among two large matrices” ( Bykhovskaya and Gorin 2025 ) . In JEPA, the objective is the same except the second data matrix happens to be simply a different view of the same data in the first dataset (e.g. via data augmentation or spatial or temporal proximity). One of the recent papers to acknowledge a connection states, “JEPA-based models implicitly perform a non-linear generalization of Canonical Correlation Analysis”. ( Huang 2026 ) CCA’s connection to JEPA is relevant to Schmidhuber’s debate on who invented JEPA , which is directed at Yann LeCun.…