The United Nations estimates that some 40% of languages spoken around the world face extinction. Can artificial intelligence slow this trend?
As much as global tech giants like to think so, the reality is not that simple. The recent crop of generative AI tools have shown remarkable gains in breaking down language and cultural barriers. But there are major gaps when it comes to understanding so-called low-resource languages, such as indigenous and regional dialects at risk of dying out, which lack meaningful digital representation.
A report from Stanford’s Institute for Human Centered Artificial Intelligence earlier this year found that most major large-language models, or LLMs, underperform in non-English, and especially in resource-scarce vernacular.
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