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Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [6] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [4]
By utilizing a pre-trained image diffusion model as a base generator, the model efficiently generated high-quality and coherent videos. Fine-tuning the pre-trained model on video data addressed the domain gap between image and video data, enhancing the model's ability to produce realistic and consistent video sequences. [ 14 ]
Throughout its history, artificial intelligence art has raised many philosophical concerns related to the human mind, artificial beings, and what can be considered art in a human–AI collaboration. Since the 20th century, artists have used AI to create art, some of which has been exhibited in museums and won awards. [1]
Producing high-quality visual art is a prominent application of generative AI. [53] Generative AI systems trained on sets of images with text captions include Imagen, DALL-E, Midjourney, Adobe Firefly, FLUX.1, Stable Diffusion and others (see Artificial intelligence art, Generative art, and Synthetic media).
Firefly expanded its capabilities to Illustrator, Premiere Pro, and Express, particularly for generating photos, videos and audio to enhance or alter specific parts of the media. NVIDIA Picasso runs some Adobe Firefly models. [10] Google planned to use Firefly in Bard (now Gemini) as its AI image generator, but ended up using their own Imagen ...
"Generative art" often refers to algorithmic art (algorithmically determined computer generated artwork) and synthetic media (general term for any algorithmically generated media), but artists can also make generative art using systems of chemistry, biology, mechanics and robotics, smart materials, manual randomization, mathematics, data ...
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