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For AI art generation, which generates images from text prompts, NovelAI uses a custom version of the source-available Stable Diffusion [2] [14] text-to-image diffusion model called NovelAI Diffusion, which is trained on a Danbooru-based [5] [1] [15] [16] dataset. NovelAI is also capable of generating a new image based on an existing image. [17]
Quick, Draw! is an online guessing game developed and published by Google LLC that challenges players to draw a picture of an object or idea and then uses a neural network artificial intelligence to guess what the drawings represent. [2] [3] [4] The AI learns from each drawing, improving its ability to guess correctly in the future. [3]
A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [3] providing relevant context, or describing a character for the AI to mimic. [1]
The Draw-A-Scientist Test (DAST) is an open-ended projective test designed to investigate children's perceptions of the scientist. Originally developed by David Wade Chambers in 1983, the main purpose was to learn at what age the well known stereotypic image of the scientist first appeared.
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An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
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