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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.
DALL-E was revealed by OpenAI in a blog post on 5 January 2021, and uses a version of GPT-3 [5] modified to generate images.. On 6 April 2022, OpenAI announced DALL-E 2, a successor designed to generate more realistic images at higher resolutions that "can combine concepts, attributes, and styles". [6]
Midjourney is a generative artificial intelligence program and service created and hosted by the San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called prompts, similar to OpenAI's DALL-E and Stability AI's Stable Diffusion.
AI generated images have become much more advanced. 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.
AI Dungeon is a text adventure game that uses artificial intelligence to generate random storylines in response to player-submitted stimuli. [1] [2] [3] [4]In the game, players are prompted to choose a setting for their adventure (e.g. fantasy, mystery, apocalyptic, cyberpunk, zombies), [5] [6] followed by other options relevant to the setting (such as character class for fantasy settings).
The procedural generation system in roguelikes would create dungeons in ASCII- or regular tile-based systems and define rooms, hallways, monsters, and treasure to challenge the player. Roguelikes, and games based on the roguelike concepts, allow the development of complex gameplay without having to spend excessive time in creating a game's world.
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The GAN uses a "generator" to create new images and a "discriminator" to decide which created images are considered successful. [32] Unlike previous algorithmic art that followed hand-coded rules, generative adversarial networks could learn a specific aesthetic by analyzing a dataset of example images.
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