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  2. Hallucination (artificial intelligence) - Wikipedia

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

    Errors in encoding and decoding between text and representations can cause hallucinations. When encoders learn the wrong correlations between different parts of the training data, it could result in an erroneous generation that diverges from the input. The decoder takes the encoded input from the encoder and generates the final target sequence.

  3. AI slop - Wikipedia

    en.wikipedia.org/wiki/AI_slop

    "AI slop", often simply "slop", is a term for low-quality media, including writing and images, made using generative artificial intelligence technology. [ 4 ] [ 5 ] [ 1 ] Coined in the 2020s, the term has a derogatory connotation akin to " spam ".

  4. Google making changes after Gemini AI portrayed people of ...

    www.aol.com/news/google-making-changes-gemini-ai...

    Google is one of many tech companies that are feverishly competing to develop the best generative AI systems that can create text, images and video from simple prompts.

  5. AI Testing Mostly Uses English Right Now. That's Risky - AOL

    www.aol.com/ai-testing-mostly-uses-english...

    As AI develops, so too does its massively unreported language issue, writes Hamza Chaudhry.

  6. Impossible color - Wikipedia

    en.wikipedia.org/wiki/Impossible_color

    A fictitious color or imaginary color is a point in a color space that corresponds to combinations of cone cell responses in one eye that cannot be produced by the eye in normal circumstances seeing any possible light spectrum. [4] No physical object can have an imaginary color.

  7. How Sam Altman got it wrong on a key part of AI ... - AOL

    www.aol.com/finance/sam-altman-got-wrong-key...

    DALL-E, the company’s image generation tool, can create art from text prompts. GPT-4, the latest model of ChatGPT , can write bedtime stories, poetry, and song lyrics.

  8. OpenAI CEO Sam Altman says AI can go ‘quite wrong’ while ...

    www.aol.com/openai-ceo-sam-altman-says-221125962...

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  9. Affective computing - Wikipedia

    en.wikipedia.org/wiki/Affective_computing

    It shows that converting the pixel color of the standard RGB color space to a color space such as oRGB color space [43] or LMS channels perform better when dealing with faces. [44] So, map the above vector onto the better color space and decompose into red-green and yellow-blue channels. Then use deep learning methods to find equivalent emotions.