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The Winograd schema challenge (WSC) is a test of machine intelligence proposed in 2012 by Hector Levesque, a computer scientist at the University of Toronto.Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what are called Winograd schemas, named after Terry Winograd, professor of computer ...
Artificial intelligence. Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is artificial intelligence capable of generating text, images, videos, or other data using generative models, [2] often in response to prompts. [3][4] Generative AI models learn the patterns and structure of their input training data and then generate ...
Natural language processing (NLP) is an interdisciplinary subfield of computer science and 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.
The algorithm underlying the software studied a vast pool of proper sentences in English and builds a model of proper language. The software does not analyze the text at the level of the word, but of the whole sentence. Dyslectics can have trouble choosing the right word – hence the attention to the sentence as a whole. [10]
Text segmentation is the process of dividing written text into meaningful units, such as words, sentences, or topics. The term applies both to mental processes used by humans when reading text, and to artificial processes implemented in computers, which are the subject of natural language processing. The problem is non-trivial, because while ...
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
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