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  2. Undetectable.ai - Wikipedia

    en.wikipedia.org/wiki/Undetectable.ai

    Undetectable AI (or Undetectable.ai) is an artificial intelligence content detection and modification software designed to identify and alter artificially generated text, such as that produced by large language models.

  3. Artificial intelligence content detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence...

    Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI).. However, the reliability of such software is a topic of debate, [1] and there are concerns about the potential misapplication of AI detection software by educators.

  4. 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), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.

  5. "Human … Please die": Chatbot responds with ... - AOL

    www.aol.com/human-please-die-chatbot-responds...

    In an online conversation about aging adults, Google's Gemini AI chatbot responded with a threatening message, telling the user to "please die." "Human … Please die": Chatbot responds with ...

  6. ChatGPT boss says he’s created human-level AI, then says he’s ...

    www.aol.com/chatgpt-boss-says-created-human...

    OpenAI founder Sam Altman, whose company created the viral AI chatbot ChatGPT, announced on Tuesday that his firm had achieved human-level artificial intelligence, before claiming that he was ...

  7. Content similarity detection - Wikipedia

    en.wikipedia.org/wiki/Content_similarity_detection

    Tokens – as with strings, but using a lexer to convert the program into tokens first. This discards whitespace, comments, and identifier names, making the system more robust against simple text replacements. Most academic plagiarism detection systems work at this level, using different algorithms to measure the similarity between token sequences.

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