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Software Developer First public release Latest stable version License Deployment options Scripts supported Notes Copyscape: Indigo Stream Technologies, Ltd.
Copyleaks is a plagiarism detection platform that uses artificial intelligence (AI) to identify similar and identical content across various formats. [ 1 ] [ 2 ] Copyleaks was founded in 2015 by Alon Yamin and Yehonatan Bitton, software developers working with text analysis, AI, machine learning, and other cutting-edge technologies.
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.
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]
In November 2023, EarthWeb used Undetectable.ai alongside GPTZero to analyze celebrity apology statements. [17] [18]In January 2024, SourceFed announced plans to use Undetectable.ai for AI content detection.
GPTZero uses qualities it terms perplexity and burstiness to attempt determining if a passage was written by a AI. [14] According to the company, perplexity is how random the text in the sentence is, and whether the way the sentence is constructed is unusual or "surprising" for the application.
Given the high rate of false positives, deleting or tagging content purely because it was flagged by an automatic AI detector is not acceptable. When missing more precise information, AI will often describe in detail very generic and common features, praising a village for its fertile farmlands, livestock and scenic countryside despite it being ...
F(0) = 1.0; D(0) = 1.0; i = 0 while F(i) > Ftarget increase i n(i) = 0; F(i)= F(i-1) while F(i) > f × F(i-1) increase n(i) use P and N to train a classifier with n(i) features using AdaBoost Evaluate current cascaded classifier on validation set to determine F(i) and D(i) decrease threshold for the ith classifier (i.e. how many weak ...