The update equations going from time step t to t + 1 in stochastic gradient descent Figure 6 .14 Intuition of one step of gradient descent. The skip-gram model tries to shift embeddings so the target embeddings (here for apricot) are closer to (have a higher dot product with) context embeddings for nearby words (here jam) and further from (lower dot product with) context embeddings for noise words that don't occur nearby (here Tolstoy and matrix).