Risk · 3 min read
It has become almost routine to describe the next generation of AI models as increasingly global. Models write in dozens of languages, answer questions about faraway places, and move fluidly across translation, summarization, coding, and reasoning tasks.
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It has become almost routine to describe the next generation of AI models as increasingly global. Models write in dozens of languages, answer questions about faraway places, and move fluidly across translation, summarization, coding, and reasoning tasks.
But there is a gap between multilingual fluency and world representation. A model can sound fluent in many languages while still learning from a narrow view of the world.
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