Smartling VP Olga Beregovaya says the reason frontier AI is still Anglo-centric is surprisingly simple: translation isn’t a priority. "I may make a controversial statement. If you look at frontier models, usually translation is not the main objective. If a model is to perform 1,000 tasks, translation is just one of 1,000." "Since translation is an afterthought, I would say long tail under-resourced languages translation is a layer below the afterthought." "With each next release, discoveries are made through evals that the languages underperform, and for most of the models, long-tail language performance starts evolving." "The more models translate, the more people read, the more people react, so the training data is just increasing. I'm gonna write on social media about it, and hey, what did I just do? I just provided additional customization data. It's a compounding effect." @smartling