This chapter provides an introduction to more advanced, hierarchically structured information granules such as those of higher type and higher order. Hybridization is about bringing several formalisms of information granules and using them in an orthogonal setting. In general, when talking about information granules of higher type, that is, type-2, the chapter presents information granules whose elements are characterized by membership grades, which themselves are information granules, For instance, in type-2 fuzzy sets, membership grades are quantified as fuzzy sets or intervals in the unit interval. The chapter describes concepts and form models using several formalisms of information granularity. These constructs become of particular interest when information granules have to capture a multifaceted nature of the problem. The chapter shows that the probabilistic–linguistic synergy, some other alternatives might be worth pursuing. It determines that results for logic operations on probabilistic sets, assuming that the corresponding probabilistic characteristics are available.