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2. 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.

3. Hallucination (artificial intelligence) - Wikipedia

   en.wikipedia.org/wiki/Hallucination_(artificial...

   Plagiarism detectors gave the generated articles an originality score of 100%, meaning that the information presented appears to be completely original. Other software designed to detect AI generated text was only able to correctly identify these generated articles with an accuracy of 66%.

4. Natural language generation - Wikipedia

   en.wikipedia.org/wiki/Natural_language_generation

   Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...

5. OpenAI’s AI-generated text detector is never technically ...

   www.aol.com/news/openai-ai-generated-text...

   OpenAI’s "classifier for indicating AI-written text" is the company’s latest invention, and it’s OpenAI’s AI-generated text detector is never technically wrong, but it’s still easy to ...

6. Do AI-generated images reinforce gender and racial ... - AOL

   www.aol.com/ai-generated-images-reinforce-gender...

   AI image generators have the ability to generate visual content from text descriptions. Anyone can enter a prompt—from detailed descriptions to simple keywords—and the AI generator brings ...

7. Prompt engineering - Wikipedia

   en.wikipedia.org/wiki/Prompt_engineering

   These models take text prompts as input and use them to generate AI-generated images. Text-to-image models typically do not understand grammar and sentence structure in the same way as large language models, [48] thus may require a different set of prompting techniques. Text-to-image models do not natively understand negation.