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2. Text-to-image model - Wikipedia

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

   A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks.

3. Ideogram (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

   Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.

4. Roblox - Wikipedia

   en.wikipedia.org/wiki/Roblox

   Roblox Studio includes multiple premade game templates, [16] [17] as well as the Toolbox, which allows access to user-created models, plugins, audio, images, meshes, video, and fonts. [ 18 ] [ 19 ] Games, officially referred to as "experiences" on the platform, [ 20 ] [ 21 ] are scripted with Lua u , a dialect of the Lua programming language ...

5. Stable Diffusion - Wikipedia

   en.wikipedia.org/wiki/Stable_Diffusion

   Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom.

6. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   AI-driven image generation tools have been heavily criticized by artists because they are trained on human-made art scraped from the web." [7] The second is the trouble with copyright law and data text-to-image models are trained on. OpenAI has not released information about what dataset(s) were used to train DALL·E 2, inciting concern from ...

7. Text-to-image personalization - Wikipedia

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

   Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.