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  2. 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. The largest and most capable LLMs are generative pretrained transformers (GPTs).

  3. Wikipedia : Using neural network language models on Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Using_neural...

    With the rise of machine learning, discussions about Wikipedia and AI models are becoming more and more heated. As of December 2022, with the release of ChatGPT for free to the public, AI has shown its potential to either massively improve or disrupt Wikipedia. It is clear that research is needed in order to inform discussions surrounding ...

  4. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are common examples of foundation models.

  5. Transformer (deep learning architecture) - Wikipedia

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

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  6. Generative pre-trained transformer - Wikipedia

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

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  7. Self-supervised learning - Wikipedia

    en.wikipedia.org/wiki/Self-supervised_learning

    Autoassociative self-supervised learning is a specific category of self-supervised learning where a neural network is trained to reproduce or reconstruct its own input data. [8] In other words, the model is tasked with learning a representation of the data that captures its essential features or structure, allowing it to regenerate the original ...

  8. Language model - Wikipedia

    en.wikipedia.org/wiki/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. The largest and most capable LLMs are generative pretrained transformers (GPTs).

  9. Glossary of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_artificial...

    This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence (AI), its subdisciplines, and related fields. Related glossaries include Glossary of computer science , Glossary of robotics , and Glossary of machine vision .