Generalized linear models can be expanded in different ways to create a variety of models. In this paper, five extensions are discussed: generalized additive models, quasi-likelihood, joint modeling of mean and dispersion, hierarchical generalized linear models with extra random components, and modeling of correlated responses in longitudinal models. These extensions can be combined in various ways to form a wide range of models. Additionally, the paper briefly mentions a potential extension to dynamic forms of the models.