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  2. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]

  3. Generative artificial intelligence - Wikipedia

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

    AI generated images have become much more advanced. In 2021, the release of DALL-E, a transformer-based pixel generative model, followed by Midjourney and Stable Diffusion marked the emergence of practical high-quality artificial intelligence art from natural language prompts.

  4. 5 new AI products worth trying from the avalanche of ... - AOL

    www.aol.com/5-ai-products-worth-trying-103201896...

    Apple's iOS 18.2 software update came out Wednesday and introduced us to Genmoji, custom AI-generated emoji made possible with Apple Intelligence.. You can make a Genmoji inspired by someone you ...

  5. Synthetic media - Wikipedia

    en.wikipedia.org/wiki/Synthetic_media

    Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...

  6. It launched AI Overviews earlier this year, which are AI-generated responses that appear at the top of traditional Google Search results. Overviews can include text, images, and links to third ...

  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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