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As part of the effort, the seven companies committed to developing a system to "watermark" all forms of content, from text, images, audios, to videos generated by AI so that users will know when ...
Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI . As with other text-to-image models, Flux generates images from natural language descriptions, called prompts .
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data.
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.
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [ 7 ] 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. [ 5 ]
In August 2023, Jupyter AI, a Jupyter extension, was released. This extension incorporates generative artificial intelligence into Jupyter notebooks, enabling users to explain and generate code, rectify errors, summarize content, inquire about their local files, and generate complete notebooks based on natural language prompts.
As a leading organization in the ongoing AI boom, [7] OpenAI is known for the GPT family of large language models, the DALL-E series of text-to-image models, and a text-to-video model named Sora. [ 8 ] [ 9 ] Its release of ChatGPT in November 2022 has been credited with catalyzing widespread interest in generative AI .
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.