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Automatic & Neural Machine Translation

Automatic or machine translation is perhaps one of the most challenging artificial intelligence tasks given the fluidity of human language. Classically, rule-based systems were used for this task, which was replaced in the 1990s with statistical methods. More recently, deep neural network models achieve state-of-the-art results in a field that is aptly named neural machine translation. - Machine translation is challenging given the inherent ambiguity and flexibility of human language. - Statistical machine translation replaces classical rule-based systems with models that learn to translate from examples. - Neural machine translation models fit a single model rather than a pipeline of fine-tuned models and currently achieve state-of-the-art results.

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Automatic or machine translation is perhaps one of the most challenging artificial intelligence tasks given the fluidity of human language. Classically, rule-based systems were used for this task, which was replaced in the 1990s with statistical methods. More recently, deep neural network models achieve state-of-the-art results in a field that is aptly named neural machine translation. - Machine translation is challenging given the inherent ambiguity and flexibility of human language. - Statistical machine translation replaces classical rule-based systems with models that learn to translate from examples. - Neural machine translation models fit a single model rather than a pipeline of fine-tuned models and currently achieve state-of-the-art results.

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Artificial IntelligenceArtistMachine TranslationNeural NetworkStatistical AnalysisTranslation

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