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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. Language creation in artificial intelligence - Wikipedia

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

   When AI is used for translating between languages, it can even create a new shared language to make the process easier. Natural Language Processing (NLP) helps these systems understand and generate human-like language, making it possible for AI to interact and communicate more naturally with people.

4. List of programming languages for artificial intelligence

   en.wikipedia.org/wiki/List_of_programming...

   Prolog is particularly useful for symbolic reasoning, database and language parsing applications. Artificial Intelligence Markup Language (AIML) [11] is an XML dialect [12] for use with Artificial Linguistic Internet Computer Entity (A.L.I.C.E.)-type chatterbots. Planner is a hybrid between procedural and logical languages. It gives a ...

5. 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.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.

6. Natural language generation - Wikipedia

   en.wikipedia.org/wiki/Natural_language_generation

   Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...

7. BERT (language model) - Wikipedia

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

   BERT is meant as a general pretrained model for various applications in natural language processing. That is, after pre-training, BERT can be fine-tuned with fewer resources on smaller datasets to optimize its performance on specific tasks such as natural language inference and text classification , and sequence-to-sequence-based language ...

8. 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

9. Generative pre-trained transformer - Wikipedia

   en.wikipedia.org/wiki/Generative_pre-trained...

   Meta AI (formerly Facebook) also has a generative transformer-based foundational large language model, known as LLaMA. [48] Foundational GPTs can also employ modalities other than text, for input and/or output. GPT-4 is a multi-modal LLM that is capable of processing text and image input (though its output is limited to text). [49]