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Will artificial intelligence-powered machine translation technologies eventually surpass human translators in accuracy and productivity, and if so, what are the likely timelines for widespread adoption in professional industries?
In 2016, Google Translate started using its own neural machine translation (NMT) system, which generates translations by creating artificial neural networks that mimic how the human brain learns and stores information.
The translation industry was valued at $39.37 billion in 2020, and it's expected to grow, with machine translation serving as a valuable tool, rather than replacing human translators and interpreters entirely.
Machine translation has only captured a small fraction of the overall translation industry, despite significant improvements in recent years.
Neural machine translation produces higher-quality results, but its effectiveness depends on large datasets, which may not be available for all language pairs.
Human translators are still necessary, especially in fields that require cultural nuances and subject matter expertise.
AI's role will be supportive, augmenting human translators' work and not outright replacing them.
Machine translators leave inconsistencies between translated languages that humans can capture and improve.
Human translations are more expensive, but they produce 100% accurate content with tone and emotion that a machine can't understand.
Big data doesn't have a big sense of humor, and jokes, puns, and sly innuendo, as well as nuanced cultural references, are among the hardest bits to get over the language barrier.
Human translation doesn't just set the standard, it is the standard.
A professional human translator will not only understand it personally but will also consider the multitude of other ways the target audience could interpret it.
Even with advancements in machine translation, human translators will still be necessary to avoid embarrassing mistakes and ensure the brand's reputation.
Despite the high level of growth in machine translation, the top providers in this space, such as IBM, Microsoft, and RWS, still rely on human expertise.
Companies like Meta, Google, and Amazon are getting heavily involved in machine translation, but human translators will still be needed to ensure quality and accuracy.
The emphasis on translation technology will continue to grow, but human translators will remain essential for nuanced and culturally sensitive translations.
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