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  2. NovelAI - Wikipedia

    en.wikipedia.org/wiki/NovelAI

    NovelAI is an online cloud-based, SaaS model, and a paid subscription service for AI-assisted storywriting [2] [3] [4] and text-to-image synthesis, [5] originally launched in beta on June 15, 2021, [6] with the image generation feature being implemented later on October 3, 2022.

  3. Text-to-image model - Wikipedia

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

    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.

  4. 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.

  5. DeepSeek releases ‘revolutionary’ AI image generator amid ...

    www.aol.com/deepseek-releases-revolutionary-ai...

    Chinese AI startup DeepSeek has launched a “revolutionary” new image generator that it claims can outperform the best models built by US-based rivals at a fraction of the price.. The launch of ...

  6. Generative artificial intelligence - Wikipedia

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

    As of August 2023, more than 15 billion images had been generated using text-to-image algorithms, with 80% of these created by models based on Stable Diffusion. [ 184 ] If AI-generated content is included in new data crawls from the Internet for additional training of AI models, defects in the resulting models may occur. [ 185 ]

  7. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    CLIP is a separate model based on contrastive learning that was trained on 400 million pairs of images with text captions scraped from the Internet. Its role is to "understand and rank" DALL-E's output by predicting which caption from a list of 32,768 captions randomly selected from the dataset (of which one was the correct answer) is most ...

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