Shifting local token interactions from inference to training-time lookups seen as a scaling win

AccBalanced · x · 2026-09-12

Halvar Flake highlighted an LLM architecture optimization that converts many local token-interaction computations into straight lookups at inference time, effectively moving that calculation from inference to training. He calls it a clever trick and a blueprint for further optimizations, suggesting LLM architectures still have substantial room to improve. The reposter frames it as a "massive scaling win."

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