Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
For most of the last six years, the most capable LLMs were locked behind APIs. You could call them, you could build on them, but you couldn’t look inside, customize
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 expensive. The data needs are enormous. And you can’t bootstrap from a “close enough” language without inheriting serious bias. A
