# YAML, Json, and Language Modeling: a read

> In conclusion, while JSON is generally faster to parse and consume than YAML, YAML is significantly more cost/time-efficient than JSON and can help language models produce precisely the same content faster and cheaper. Essentially, it is more efficient to request YAML, and convert the result to JSON on the code-side, instead of requesting JSON directly. It is worth mentioning that the potential compromise might be the strictness of JSON for some formats (numbers could be printed as strings, surrounded with quotes). This can be solved by providing schema or post-parsing the fields into the right data type. Regardless, it could be good practice anyway to enforce data type conversions on code-side. -- Elya Livshitz
=> https://betterprogramming.pub/yaml-vs-json-which-is-more-efficient-for-language-models-5bc11dd0f6df

I sent this link to a friend who has hired an AI company to build a customized language model. I barely grok the tokenization stuff, but I get the gist. The author provides convincing test results.

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