
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

Here’s a problem that doesn’t always make it into model deployment conversations: AI models degrade over time, even when you don’t touch them. Not because the model changes. Because the world does. This is concept drift — when the relationship between the inputs a model was trained on and the
