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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.

  3. 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.

  4. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    There are two LLMs. One is the target LLM, and another is the prompting LLM. Prompting LLM is presented with example input-output pairs, and asked to generate instructions that could have caused a model following the instructions to generate the outputs, given the inputs.

  5. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    A generative LLM can be prompted in a zero-shot fashion by just asking it to translate a text into another language without giving any further examples in the prompt. Or one can include one or several example translations in the prompt before asking to translate the text in question. This is then called one-shot or few-shot learning, respectively.

  6. List of large language models - Wikipedia

    en.wikipedia.org/wiki/List_of_large_language_models

    LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. This page lists notable large language models. For the training cost column, 1 petaFLOP-day = 1 petaFLOP/sec × 1 day = 8.64E19 FLOP. Also, only the largest model's cost is written.

  7. PwC is using 'prompting parties' to teach employees how to ...

    www.aol.com/pwc-using-prompting-parties-teach...

    PwC hosts "prompting parties" to help employees experiment with generative AI tools. The firm's chief learning officer said employees needed a safe, low-stakes format to experiment with it.

  8. College Football Playoff: Bettors like Ohio State in the ...

    www.aol.com/sports/college-football-playoff...

    Two-thirds of the bets and money are on a low-scoring game, and the total has moved significantly as a result. The over/under opened at 50.5 and has dropped to 45.5. Even more bettors are backing ...

  9. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    GPT-3 is capable of performing zero-shot and few-shot learning (including one-shot). [ 1 ] In June 2022, Almira Osmanovic Thunström wrote that GPT-3 was the primary author on an article on itself, that they had submitted it for publication, [ 24 ] and that it had been pre-published while waiting for completion of its review.