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  2. DeepL Translator - Wikipedia

    en.wikipedia.org/wiki/DeepL_Translator

    DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne -based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL. It initially offered translations between seven European languages and has since gradually expanded to support 33 languages.

  3. DeepL schools other online translators with clever machine ...

    techcrunch.com/2017/08/29/deepl-schools-other...

    DeepL was born from the similarly excellent Linguee, a translation tool that has existed for years and, while popular, never quite reached the level of Google Translate — the latter has a huge ...

  4. DeepL, the AI-based language translator, raises over $100M at ...

    techcrunch.com/2023/01/11/deepl-the-ai-based...

    DeepL, a startup that provides instant translation-as-a-service both to businesses and to individuals — competing with Google, Bing and other online tools — has confirmed a fundraise at a €1 ...

  5. DeepL takes aim at Grammarly with the launch of Write, to ...

    techcrunch.com/2023/01/17/deepl-takes-aim-at...

    Indeed, for many, DeepL’s neural network-based translator works better than these others, capturing certain nuances and meanings that rivals have missed. That approach, it seems, is now the ...

  6. Machine translation - Wikipedia

    en.wikipedia.org/wiki/Machine_translation

    Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation [1] and large language models ...

  7. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Neural machine translation ( NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. It is the dominant approach today [ 1]: 293 [ 2]: 1 and can produce translations that rival human translations when ...

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