Translating terms like 'dim sum' poses challenges for AI models, which often struggle with cultural nuances. Developers like Jacky Chan highlight that machine-generated translations can feel unnatural and may include mistranslations. AI encounters problems with low-resource languages due to limited data, resulting in translations that native speakers may not recognize. As digital resources primarily favor English, non-English languages, especially those less represented online, suffer from inadequate training datasets, complicating the translation process and reducing overall accuracy for AI models.
Many machine-created datasets could feature mistranslations, words that no native speaker actually uses in a specific language, posing challenges for AI's accuracy.
AI models encounter words they don't know or that don't exist in another culture, leading to fabricated translations that can compromise clarity and meaning.
Collection
[
|
...
]