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This may be directly involved with creation of text content, or in support roles related to evaluating article quality, adding metadata, or generating images. As with any machine-generated content, care must be used when employing AI at scale or in applying it where the community consensus is to exercise more caution.
With the rise of machine learning, discussions about Wikipedia and AI models are becoming more and more heated. As of December 2022, with the release of ChatGPT for free to the public, AI has shown its potential to either massively improve or disrupt Wikipedia. It is clear that research is needed in order to inform discussions surrounding ...
In 2022, the public release of ChatGPT inspired more experimentation with AI and writing Wikipedia articles. A debate was sparked about whether and to what extent such large language models are suitable for such purposes in light of their tendency to generate plausible-sounding misinformation , including fake references; to generate prose that ...
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data.
GPT-2 can generate thematically-appropriate text for a range of scenarios, even surreal ones like a CNN article about Donald Trump giving a speech praising the anime character Asuka Langley Soryu. Here, the tendency to generate nonsensical and repetitive text with increasing output length (even in the full 1.5B model) can be seen; in the second ...
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.
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