Pomegranate is a modular probabilistic modeling library that treats all models as probability distributions, enabling flexible composition of components like distributions, Bayesian networks, and hidden Markov models. The recent v1.0.0 rewrite migrated from Cython to PyTorch as the computational backend, providing GPU acceleration and modern deep learning integration while maintaining the same probabilistic modeling capabilities.