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  2. Google Translate - Wikipedia

    en.wikipedia.org/wiki/Google_Translate

    Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]

  3. 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.

  4. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    The transformer model quickly became the dominant choice for machine translation systems [2]: 44 and was still by far the most-used architecture in the Workshop on Statistical Machine Translation in 2022 and 2023. [32]: 35–40 [33]: 28–31

  5. Microsoft Translator - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Translator

    Microsoft Translator or Bing Translator is a multilingual machine translation cloud service provided by Microsoft.Microsoft Translator is a part of Microsoft Cognitive Services [1] and integrated across multiple consumer, developer, and enterprise products, including Bing, Microsoft Office, SharePoint, Microsoft Edge, Microsoft Lync, Yammer, Skype Translator, Visual Studio, and Microsoft ...

  6. Reverso (language tools) - Wikipedia

    en.wikipedia.org/wiki/Reverso_(language_tools)

    In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies. Based on content from Netflix, Fleex has expanded to also include video content from YouTube, TED Talks, and custom video files. [6] [7] [8] In 2018 it released a new mobile app, which combines translations and learning activities.

  7. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.

  8. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    On October 25, 2019, Google announced that they had started applying BERT models for English language search queries within the US. [26] On December 9, 2019, it was reported that BERT had been adopted by Google Search for over 70 languages. [27] [28] In October 2020, almost every single English-based query was processed by a BERT model. [29]

  9. Language model - Wikipedia

    en.wikipedia.org/wiki/Language_model

    A language model is a probabilistic model of a natural language. [1] In 1980, the first significant statistical language model was proposed, and during the decade IBM performed ‘Shannon-style’ experiments, in which potential sources for language modeling improvement were identified by observing and analyzing the performance of human subjects in predicting or correcting text.