Lifelong learning, which includes continual, continuous, and meta learning, accumulates and transfers the previously learned knowledge into future learning. KD does this effectively without catastrophic forgetting, and meta-learning has been used to determine what and where to make the transfer. Global distillation, knowledge distillation-based lifelong GAN, multi-model distillation, and other KD methods also address the problem of catastrophic forgetting.