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  2. FACT CHECK: Viral Threads Image Showing Elon Musk In Mesh ...

    www.aol.com/fact-check-viral-threads-image...

    A viral image shared on Threads purports to show Tesla CEO and owner of X, Elon Musk, in a short mesh shirt. View on Threads Verdict: False The claim is false, as content detection scans from Hive ...

  3. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [69] Google Photos, [70] and the Adobe Suite (Adobe Firefly). [71] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [72] language model.

  4. Artificial intelligence art - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_art

    Generative AI has been used in video game production beyond imagery, especially for level design (e.g., for custom maps) and creating new content (e.g., quests or dialogue) or interactive stories in video games. [157] [158] AI has also been used in the literary arts, [159] such as helping with writer's block, inspiration, or rewriting segments.

  5. Perplexity AI - Wikipedia

    en.wikipedia.org/wiki/Perplexity_AI

    Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries. [3] Its developer, Perplexity AI, Inc., is based in San Francisco, California . [ 4 ]

  6. Direct-to-garment printing - Wikipedia

    en.wikipedia.org/wiki/Direct-to-garment_printing

    Since D2 inks are water-based, they work best for printing on natural fibers such as cotton, bamboo, hemp, and linen. In addition, pre-treatment is typically applied to the garment before printing. The pre-treatment is heat-pressed into the custom t-shirt causing the fibers of the shirt to lay down. [2]

  7. 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.

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