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  2. Language creation in artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Language_creation_in...

    AI models could accidentally form opinions based on the language (words and sentences) from which they are trained. This is undesirable for a neutral-minded AI. It is intended to overcome these limitations and challenges in future, as the models learn more language through conversations and information they receive.

  3. Blissymbols - Wikipedia

    en.wikipedia.org/wiki/Blissymbols

    The symbol represents the expression "world language", which was a first tentative name for Blissymbols. It combines the symbol for "writing tool" or "pen" (a line inclined, as a pen being used) with the symbol for "world", which in its turn combines "ground" or "earth" (a horizontal line below) and its counterpart derivate "sky" (a horizontal ...

  4. Context-free grammar - Wikipedia

    en.wikipedia.org/wiki/Context-free_grammar

    The language generated by a grammar is the set of all strings of terminal symbols that can be derived, by repeated rule applications, from some particular nonterminal symbol ("start symbol"). Nonterminal symbols are used during the derivation process, but do not appear in its final result string.

  5. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus. Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word ...

  6. Lexical analysis - Wikipedia

    en.wikipedia.org/wiki/Lexical_analysis

    In case of a natural language, those categories include nouns, verbs, adjectives, punctuations etc. In case of a programming language, the categories include identifiers, operators, grouping symbols and data types. Lexical tokenization is related to the type of tokenization used in large language models (LLMs) but with two differences.

  7. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  8. List of writing systems - Wikipedia

    en.wikipedia.org/wiki/List_of_writing_systems

    All contain graphemes that represent phonetic (sound-based) elements as well. These phonetic elements may be used on their own (to represent, for example, grammatical inflections or foreign words), or may serve as phonetic complements to a logogram (used to specify the sound of a logogram that might otherwise represent more than one word). In ...

  9. Chomsky hierarchy - Wikipedia

    en.wikipedia.org/wiki/Chomsky_hierarchy

    The Chomsky hierarchy in the fields of formal language theory, computer science, and linguistics, is a containment hierarchy of classes of formal grammars. A formal grammar describes how to form strings from a language's vocabulary (or alphabet) that are valid according to the language's syntax.