Write a function powersarray (b) that takes a list (or 1-dimensional numpy array) of length d representing a row vector [bo, . . ., bd−1] (for some d) and returns a numpy array representing the matrix bo b-1 d-1 : bd- bd-1

Search a sorted matrix: The input consists of a real number x and a matrix A[1..n, 1..m] of nm real values, where A[i, 1..m] and A[1..n, j] are the rows and columns, respectively, of the matrix. The objective is to either state that all of the members of A are greater than x or to locate the largest array entry A[i, j] that is less than or equal to x. Create and evaluate an iterative approach for this issue that looks at the least amount of matrix entries feasible. If you think the issue can be resolved with a straightforward binary search, think twice.

Assume that EMB(w) is the word embedding for a word, w, computed by some common technique for computing word embeddings (e.g., word2vec). Consider the vector obtained by the following vector arithmetic: EMB("Japan") + EMB("Paris") - EMB("Tokyo"). Other than the words that already related to this equation, what word's embedding would likely be close to the result? Briefly explain (in one sentence) your answer.