Google addresses a longstanding limitation of RNNs by creating a model that combines strengths of both RNNs and Transformers
The new approach provides better performance than traditional RNNs while maintaining computational efficiency advantages
This hybrid architecture offers a practical middle ground for sequence processing tasks that don't require full Transformer complexity
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