Why are two random vectors near orthogonal in high dimensions? Introduction High-dimensional embedding vectors are fundamental building blocks in Machine Learning, particularly in transformers or word2vec . Typically, two vectors that are semantically similar point in roughly the same direction; if they are entirely dissimilar, they point in opposite directions; and if they’re nearly orthogonal,…