
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

Speed benchmarks in AI research can feel detached from anything practical. A paper claims a 10x speedup and you skim past it because the benchmarks never quite match the thing you’re actually trying to do. The FlexGNN result — up to 95.5x faster training on large graphs — is worth
