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  2. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text. T5 models are usually pretrained on a massive dataset of text and code, after which they can perform the text-based tasks that are similar to their pretrained tasks.

  3. 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.

  4. Artificial intelligence in fiction - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    Artificial intelligence is a recurrent theme in science fiction, whether utopian, emphasising the potential benefits, or dystopian, emphasising the dangers.. The notion of machines with human-like intelligence dates back at least to Samuel Butler's 1872 novel Erewhon.

  5. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    BookCorpus was chosen as a training dataset partly because the long passages of continuous text helped the model learn to handle long-range information. [6] It contained over 7,000 unpublished fiction books from various genres.

  6. XLNet - Wikipedia

    en.wikipedia.org/wiki/XLNet

    The XLNet was an autoregressive Transformer designed as an improvement over BERT, with 340M parameters and trained on 33 billion words.It was released on 19 June, 2019, under the Apache 2.0 license. [1]

  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. 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 often examples of foundation models.

  9. Fact and Fancy - Wikipedia

    en.wikipedia.org/wiki/Fact_and_Fancy

    Fact and Fancy is a collection of seventeen scientific essays by American writer and scientist Isaac Asimov. It was the first in a series of books collecting his essays from The Magazine of Fantasy and Science Fiction, and Asimov's second book of science essays altogether (after Only a Trillion). Doubleday & Company first published it in March ...