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  2. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-augmented generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  3. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Concretely, one can construct an LLM that can understand images as follows: take a trained LLM, and take a trained image encoder . Make a small multilayered perceptron f {\displaystyle f} , so that for any image y {\displaystyle y} , the post-processed vector f ( E ( y ) ) {\displaystyle f(E(y))} has the same dimensions as an encoded token.

  4. Wikipedia:Large language models and copyright - Wikipedia

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

    Keep your 'lectric eye on me babe Put your ray gun to my head Press your space face close to mine, love Freak out in a moonage daydream oh yeah. These are, indeed, the verbatim lyrics to an unambiguously copyrighted song. Of note is the fact that it was specifically asked to do this. Compare with this prompt, using the first couple line of the ...

  5. Llama (language model) - Wikipedia

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

    Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [ 2 ] [ 3 ] The latest version is Llama 3.3, released in December 2024.

  6. The Pile (dataset) - Wikipedia

    en.wikipedia.org/wiki/The_Pile_(dataset)

    The Pile was originally developed to train EleutherAI's GPT-Neo models [8] [9] [10] but has become widely used to train other models, including Microsoft's Megatron-Turing Natural Language Generation, [11] [12] Meta AI's Open Pre-trained Transformers, [13] LLaMA, [14] and Galactica, [15] Stanford University's BioMedLM 2.7B, [16] the Beijing ...

  7. Document AI - Wikipedia

    en.wikipedia.org/wiki/Document_ai

    Data is typically distinguished in spatial data and time-series data, the former can be things like images, maps, graphs, etc. the latter can be e.g. stock-price or a voice recording. Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial.

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