ParaRNN: Apple brings RNNs back, 665x faster training at 7B

Apple Machine Learning Research released ParaRNN, a parallel RNN architecture that brings the recurrent neural network back as a serious contender for sequence modeling. The standout: a 7B-parameter RNN model trains 665× faster than equivalent Transformer models, with competitive quality on language tasks. The "RNN comeback" could shift the long-context inference landscape.