Both applications can automatically detect languages. They use AI to translate user-provided text from one language to another.
Google Translate and DeepL are both machine translation services. By using state-of-the-art AI trained on manually translated text, it’s possible to use AI to translate new strings of text provided by a user.ĭeepL, however, seems to have found a better combination of algorithm design and language data - and there’s some evidence that it may be significantly more accurate than Google Translate. Both DeepL Translator and Google Translate use the same approach to machine translation. The tool - developed by a Cologne-based team of around 20 people - was quickly found to be just as effective as Google Translate, the older translation tool developed by one of the giants of the tech world. The machine translation service DeepL caused a major stir when it was first launched back in 2017.
When you buy through links on our site, we may earn an affiliate commision. So next time you translate a sentence or webpage with Google Translate, think about those millions of documents and billions of patterns that ultimately led to your translation - and all of it happening in the blink of an eye."Īlso, worth thinking about - more and more quality translated texts (like the UN translations, or professional TV show/movie translations) will be added further adding to the quality of google translate.įurther, the "languages of the future" will most likely be the ones with large available quality internet material, along with large amounts of quality translations available for coding by a large enough base of programmers: English, Mandarin, Spanish, German, French, Russian, Japanese.Revolutionized is reader-supported. We know our translations aren't always perfect but by constantly providing new translated texts we can make our computers smarter and our translations better. This is why our translation quality will vary by language and language pair. When you repeat this process billions of times you end up with billions of patterns and one very smart computer program.įor some languages however we have fewer translated documents available and therefore fewer patterns that our software has detected. Once the computer finds a pattern, it can use this pattern to translate similar texts in the future. Our computers scan these texts looking for statistically significant patterns - that is to say, patterns between the translation and the original text that are unlikely to occur by chance. These translated texts come from books, organizations like the UN and websites from all around the world. They do this by analyzing millions and millions of documents that have already been translated by human translators. "Instead of trying to teach our computers all the rules of a language, we let our computers discover the rules for themselves.
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