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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.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.

  3. History of natural language processing - Wikipedia

    en.wikipedia.org/wiki/History_of_natural...

    Timeline of natural language processing models. In 1990, the Elman network, using a recurrent neural network, encoded each word in a training set as a vector, called a word embedding, and the whole vocabulary as a vector database, allowing it to perform such tasks as sequence-predictions that are beyond the power of a simple multilayer perceptron.

  4. History of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/History_of_artificial...

    The recent AI boom, initiated by the development of transformer architecture, led to the rapid scaling and public releases of large language models (LLMs) like ChatGPT. These models exhibit human-like traits of knowledge, attention, and creativity, and have been integrated into various sectors, fueling exponential investment in AI.

  5. 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.

  6. 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 ...

  7. The next wave of AI won’t be driven by LLMs. Here’s what ...

    www.aol.com/finance/next-wave-ai-won-t-100327006...

    LLMs are incredibly resource-intensive, but the future of AI may lie in building models that are more powerful while being less costly and easier to deploy. Rather than making models bigger, the ...

  8. CEO of a $4.5 billion AI company reveals his 6 ... - AOL

    www.aol.com/news/ceo-4-5-billion-ai-194834363.html

    Elon Musk, who has admitted he tends to be optimistic about timelines, ... In Hugging Face's June LLM Leaderboard, which compares the performance of major open-sourced LLMs, Alibaba's Qwen2 topped ...

  9. Language model - Wikipedia

    en.wikipedia.org/wiki/Language_model

    A language model is a probabilistic model of a natural language. [1] In 1980, the first significant statistical language model was proposed, and during the decade IBM performed ‘Shannon-style’ experiments, in which potential sources for language modeling improvement were identified by observing and analyzing the performance of human subjects in predicting or correcting text.