
The 42× number that should change how you scope annotation projects
If you’ve worked on NLP for low-resource languages — Yoruba, Quechua, Tigrinya, Hmong — you know the math is brutal. Native speakers with domain expertise are scarce. Their time is
Booth 21-25 | AI Data Management Zone | Tokyo Big Sight

If you’ve worked on NLP for low-resource languages — Yoruba, Quechua, Tigrinya, Hmong — you know the math is brutal. Native speakers with domain expertise are scarce. Their time is

The “more data wins” era is mostly over. What’s replacing it is messier and more interesting: a stack of techniques — fine-tuning, preference optimization, retrieval — each with its own cost curve, its own failure modes, and its own demands on data quality. Pick the wrong lever and you can
