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  2. Jake Elwes - Wikipedia

    en.wikipedia.org/wiki/Jake_Elwes

    A.I. Interprets A.I. Interpreting ‘Against Interpretation (Sontag 1966) is a three-channel video artwork where an AI interprets Susan Sontag’s essay into images, and then and another AI reinterprets those images back into language. The piece highlights how AI-generated art can misinterpret and introduce bias. [58] [59]

  3. Midjourney - Wikipedia

    en.wikipedia.org/wiki/Midjourney

    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.

  4. Computer vision - Wikipedia

    en.wikipedia.org/wiki/Computer_vision

    In image processing, the input is an image and the output is an image as well, whereas in computer vision, an image or a video is taken as an input and the output could be an enhanced image, an understanding of the content of an image or even behavior of a computer system based on such understanding.

  5. 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.

  6. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    Image Featurizer: CLIP's image encoder can be adapted as a pre-trained image featurizer. This can then be fed into other AI models. [1] Text-to-Image Generation: Models like Stable Diffusion use CLIP's text encoder to transform text prompts into embeddings for image generation. [3]

  7. Could AI 'Rewrite' Human Identity in 2025? Reconciling Chaos ...

    www.aol.com/could-ai-rewrite-human-identity...

    Machine-learning models can generate images or compose music, apparently from thin air. But these outputs remain anchored in training data—patterns and examples curated by humans.