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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.
One part of the study assigned one group of students to write a paper. These students were first educated about plagiarism and informed that their work was to be run through a content similarity detection system. A second group of students was assigned to write a paper without any information about plagiarism.
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
If a third-party library implements a class that cannot be modified, a client cannot use an instance of it with an interface unknown to that library even if the class satisfies the interface requirements. A common solution to this problem is the adapter pattern. In contrast, with duck typing, the object would be accepted directly without the ...
ChatGPT is a generative artificial intelligence chatbot 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. [2]
ChatGPT and its ilk are largely general-purpose tools, but companies are working on more targeted generative AI platforms that could prove to be helpful in areas including medicine.
In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.
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