First Look: Facebook’s new AI Language Engine
Facebook is expected to have 2 billion monthly users by 2018. The billions of active users live in different regions and speak different languages. Facebook allows each user to translate the posts and content appearing in his new feed simply by clicking on a button. Recently, Facebook started using advanced artificial intelligence (AI) engine called DeepText. DeepText uses deep learning techniques to understand and translate text more precisely. Also, it enables various Facebook applications to speedup content translation. It even makes the translated content meaningful and relevant for users by understanding the meaning and context of the source text.
Brier Overview of Facebook’s New Text Understanding AI Engine
Uses Deep Learning Techniques
DeepText uses deep learning to understand the meaning and context of text more precisely. Deep Learning enables the engine to solve tricky language challenges. The engine is even developed based on extended deep learning ideas to understand text written in varying language and use the labelled data more efficiently. DeepText even has the capability to understand the meaning as well as sentiment behind the text. Facebook will keep using advanced deep learning techniques to make DeepText understands both textual and visual content in near future.
Understands and Translates Text Faster
Unlike conventional NLP techniques, DeepText does not rely on language-dependent knowledge. It uses deep learning to understand the meaning and context of content without any additional text reprocessing. The deep learning techniques help the engine to scan text written in multiple languages more quickly. DeepText can even translate the text in a faster but more meaningful way. According to the information provided by Facebook, DeepText has the capability to translate thousands of text written in 20 distinct languages per second.
Captures Semantic Meaning of Text
DeepText understands the text by integrating deep learning with a robust mathematical concept called word embedding. Word embedding helps the AI engine to capture the semantic meaning of word while preserving their semantic relationship. The mathematical concept even enables DeepText to understand the semantic relationship between words across multiple languages. The features help the AI engine to deliver meaningful translated content by building language-agnostic models.
Extracts Structure from Unlabelled Text
DeepText can further understand and translate both labelled and unlabelled text efficiently. DeepText combines unsupervised learning and word embedding to understand the unlabelled text precisely and extract varying structures from the unlabelled text. At the same time, it uses deep learning techniques to process the word embedding and refine them with small labelled data sets. It even combines supervised and unsupervised learning to overcome the scarcity of labelled data sets.
Facebook has already started assessing user experience by integrating DeepText with major applications like Messenger. The company further aims to keep improving the text understanding AI Engine in collaboration with the Facebook AI Research group. The upcoming version of DeepText will have the capability to understand users’ interests as well as visual content. Many analysts believe that Facebook will use its in-house engine as an effective tool to compete with other social networks and search engine. Hence, DeepText will soon enable Facebook users to translate their news feed content more precisely.
Contented by: Pmsltech.
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