In the podcast, I mentioned tensor as a multidimensional array to simplify the concept and introduce it to a wider audience. Our algorithms certainly treat tensor as a multilinear map and we design efficient decomposition methods. Most importantly, we do not form these tensors, meaning we do not instantiate them as multidimensional arrays. Instead, we implicitly manipulate the data to obtain decompositions of tensors that model higher order relationships in data.