[r/LocalLLaMA] From FlashLM to State Flow Machine: stopped optimizing transformers, started replacing them. First result: 79% length retention vs transformers' 2%

Summary

A researcher, previously known for the FlashLM series, has shifted from optimizing transformers to developing entirely new language model architectures. Their latest "State Flow Machine" approach, which avoids attention and convolution, has demonstrated a remarkable 79% length retention compared to transformers' 2%. This development suggests a potentially significant alternative to current transformer-based models, particularly in handling long contexts efficiently.

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