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2. Generative artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Generative_artificial...

   In 2021, the release of DALL-E, a transformer-based pixel generative model, followed by Midjourney and Stable Diffusion marked the emergence of practical high-quality artificial intelligence art from natural language prompts. In 2022, the public release of ChatGPT popularized the use of generative AI for general-purpose text-based tasks. [42]

3. Text-to-image model - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_model

   Text-to-image models are trained on large datasets of (text, image) pairs, often scraped from the web. With their 2022 Imagen model, Google Brain reported positive results from using a large language model trained separately on a text-only corpus (with its weights subsequently frozen), a departure from the theretofore standard approach. [18]

4. Artificial intelligence art - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence_art

   Generative AI has been used in video game production beyond imagery, especially for level design (e.g., for custom maps) and creating new content (e.g., quests or dialogue) or interactive stories in video games. [157] [158] AI has also been used in the literary arts, [159] such as helping with writer's block, inspiration, or rewriting segments.

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   You can choose from a slew of free background images, custom sounds and color options, plus enjoy advanced mail filtering, which lets you see every single attachment and image ever received from ...

6. Personalize your background image, sounds, and toolbar ...

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   1. Sign in to Desktop Gold. 2. Click the Settings button. 3. Click Personalization. 4. Click the Sounds tab. 5. Click Customize My Sounds. 6. Search for a sound or select a category from the "All" menu at the top-right.

7. Rendering (computer graphics) - Wikipedia

   en.wikipedia.org/wiki/Rendering_(computer_graphics)

   A drawback of the basic z-buffer algorithm is that each pixel ends up either entirely covered by a single object or filled with the background color, causing jagged edges in the final image. Early anti-aliasing approaches addressed this by detecting when a pixel is partially covered by a shape, and calculating the covered area.