Griffin Models: Outperforming Transformers with Scalable AI Innovation | HackerNoon
Briefly

"Our findings showcase that recurrent models can scale as efficiently as transformers, indicating a paradigm shift in how we view model effectiveness across various tasks."
"Through innovative model parallelism techniques, we demonstrate efficient training of recurrent models on-device, which significantly enhances performance for long sequences compared to traditional methods."
Read at Hackernoon
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