Research2d ago
Apple Unlocks Parallel Training For Large RNNs
ParaRNN enables the parallel training of nonlinear Recurrent Neural Networks, removing the sequential bottleneck that previously limited their scale. This architecture matches the training efficiency of Transformers while maintaining the low-memory inference typical of RNNs. It offers Apple and other developers a viable alternative for deploying large models on resource-constrained hardware.