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  2. Natural language processing - Wikipedia

    en.wikipedia.org/wiki/Natural_language_processing

    Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.

  3. Ubiquitous Knowledge Processing Lab - Wikipedia

    en.wikipedia.org/wiki/Ubiquitous_Knowledge...

    A strong focus at UKP Lab is on utilizing novel natural language processing algorithms in real-life applications. UKP Lab collaborates with partners from academia and industry to improve various application scenarios, such as customer relationship management, digital humanities, educational applications, or public security.

  4. Applications of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Applications_of_artificial...

    Transportation's complexity means that in most cases training an AI in a real-world driving environment is impractical. Simulator-based testing can reduce the risks of on-road training. [323] AI underpins self-driving vehicles. Companies involved with AI include Tesla, Waymo, and General Motors. AI-based systems control functions such as ...

  5. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    The transformer has had great success in natural language processing (NLP). Many large language models such as GPT-2, GPT-3, GPT-4, AlbertAGPT, Claude, BERT, XLNet, RoBERTa and ChatGPT demonstrate the ability of transformers to perform a wide variety of NLP-related subtasks and their related real-world applications, including: machine translation

  6. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    The use of multi-sense embeddings is known to improve performance in several NLP tasks, such as part-of-speech tagging, semantic relation identification, semantic relatedness, named entity recognition and sentiment analysis. [38] [39] As of the late 2010s, contextually-meaningful embeddings such as ELMo and BERT have been developed. [40]

  7. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    In 1987, Robert B. Allen demonstrated the use of feed-forward neural networks for translating auto-generated English sentences with a limited vocabulary of 31 words into Spanish. In this experiment, the size of the network's input and output layers was chosen to be just large enough for the longest sentences in the source and target language ...

  8. Question answering - Wikipedia

    en.wikipedia.org/wiki/Question_answering

    Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP) that is concerned with building systems that automatically answer questions that are posed by humans in a natural language.

  9. Natural-language programming - Wikipedia

    en.wikipedia.org/wiki/Natural-language_programming

    Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural language programming is not to be mixed up with ...