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  2. Artificial intelligence content detection - Wikipedia

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

    Multiple AI detection tools have been demonstrated to be unreliable in terms of accurately and comprehensively detecting AI-generated text. In a study conducted by Weber-Wulff et al., and published in 2023, researchers evaluated 14 detection tools including Turnitin and GPT Zero, and found that "all scored below 80% of accuracy and only 5 over 70%."

  3. 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.

  4. Content similarity detection - Wikipedia

    en.wikipedia.org/wiki/Content_similarity_detection

    Systems for text similarity detection implement one of two generic detection approaches, one being external, the other being intrinsic. [5] External detection systems compare a suspicious document with a reference collection, which is a set of documents assumed to be genuine. [6]

  5. Analysts at International Data Corp. (IDC), a provider of market intelligence, predict that worldwide revenues for the AI market could reach $900 billion by 2026, logging a compound annual growth ...

  6. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  7. Deepfake - Wikipedia

    en.wikipedia.org/wiki/Deepfake

    In order to assess the most effective algorithms for detecting deepfakes, a coalition of leading technology companies hosted the Deepfake Detection Challenge to accelerate the technology for identifying manipulated content. [173] The winning model of the Deepfake Detection Challenge was 65% accurate on the holdout set of 4,000 videos. [174]

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