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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 ...
Generative grammar is a research tradition in linguistics that aims to explain the cognitive basis of language by formulating and testing explicit models of humans' subconscious grammatical knowledge. Generative linguists, or generativists (/ ˈdʒɛnərətɪvɪsts /), [1] tend to share certain working assumptions such as the competence ...
Transformational grammar. In linguistics, transformational grammar (TG) or transformational-generative grammar (TGG) is part of the theory of generative grammar, especially of natural languages. It considers grammar to be a system of rules that generate exactly those combinations of words that form grammatical sentences in a given language and ...
In formal language theory, a context-free grammar (CFG) is a formal grammar whose production rules can be applied to a nonterminal symbol regardless of its context. In particular, in a context-free grammar, each production rule is of the form. with a single nonterminal symbol, and a string of terminals and/or nonterminals ( can be empty).
A generative pre-trained transformer (GPT) is a type of large language model (LLM) [1][2][3] and a prominent framework for generative artificial intelligence. [4][5] It is an artificial neural network that is used in natural language processing by machines. [6] It is based on the transformer deep learning architecture, pre-trained on large data ...
Phrase structure rules. Phrase structure rules are a type of rewrite rule used to describe a given language's syntax and are closely associated with the early stages of transformational grammar, proposed by Noam Chomsky in 1957. [1] They are used to break down a natural language sentence into its constituent parts, also known as syntactic ...
e. In natural language processing (NLP), a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
In automata theory, the class of unrestricted grammars (also called semi-Thue, type-0 or phrase structure grammars) is the most general class of grammars in the Chomsky hierarchy. No restrictions are made on the productions of an unrestricted grammar, other than each of their left-hand sides being non-empty.