Researchers have introduced byteification, a novel method that retrofits existing subword-based large language models to operate directly on raw byte encoding with minimal extra training. This approach overcomes previous performance limitations, enabling byte-level models to match traditional systems while excelling at the fine-grained character-level reasoning required for complex scientific data like computer code and biological sequences.