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  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    A prompt is natural language text describing the task that an AI should perform. [2] A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [3 ...

  3. The Pile (dataset) - Wikipedia

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

    The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]

  4. 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]

  5. These books are being used to train AI. No one told the authors

    www.aol.com/books-being-used-train-ai-120050628.html

    Nearly 200,000 books written by a wide range of authors, including Nora Roberts, are being used to train artificial intelligence systems, according to a recent report. No one asked for the writers ...

  6. Amazon hoping to train millions through free AI courses - AOL

    www.aol.com/amazon-hoping-train-millions-free...

    Amazon hopes to provide two million people with free artificial intelligence (AI) training by 2025 as part of its new “AI Ready” initiative, the e-commerce giant announced on Monday.

  7. BERT (language model) - Wikipedia

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

    High-level schematic diagram of BERT. It takes in a text, tokenizes it into a sequence of tokens, add in optional special tokens, and apply a Transformer encoder. The hidden states of the last layer can then be used as contextual word embeddings. BERT is an "encoder-only" transformer architecture. At a high level, BERT consists of 4 modules:

  8. OpenAI says it is ‘impossible’ to train AI without using ...

    www.aol.com/news/openai-says-impossible-train-ai...

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  9. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    It is a general-purpose learner and its ability to perform the various tasks was a consequence of its general ability to accurately predict the next item in a sequence, [2] [7] which enabled it to translate texts, answer questions about a topic from a text, summarize passages from a larger text, [7] and generate text output on a level sometimes ...