Research3h 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 allows RNNs to reach billions of parameters while maintaining a smaller memory footprint than Transformers. Apple researchers now provide a viable alternative for developers deploying LLMs on resource-constrained hardware.