Massive neutrinos suppress the growth of structure on small scales and leave an imprint on large-scale structure. This imprint can be measured to constrain their total mass, Mnu. With standard analyses of two-point clustering statistics, Mnu constraints are severely limited by parameter degeneracies. In this talk, I will present how the bispectrum, the next higher-order statistic, can break these degeneracies and dramatically improve constraints on Mnu and other cosmological parameters. I will then present the total information content of the redshift-space galaxy bispectrum down to nonlinear scales quantified using the Molino suite of 75,000 mock galaxy catalogs constructed from N-body simulations using the halo occupation distribution (HOD) model. Lastly, I will discuss the potential of the bispectrum for upcoming galaxy surveys such as PFS and DESI and the next steps for bispectrum analyses using simulation-based inference.