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Advancements in Language Architecture and Content Chunking
The current language architecture contains functional elements that are implemented and allocated differently. Content chunking is currently heuristic-based and hacky, but could become a learned behavior co-trained with embedding and language models. Startups like contextual AI are exploring these scenarios. Tokenization has evolved from a hacky process to a model-based approach, and similar advancements are expected in the retrieval and generation processes. While end-to-end tokenization is not widely adopted, byte pair encoding is still predominant.