Search results
Results from the WOW.Com Content Network
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.
The generator is decomposed into a pyramid of generators =, with the lowest one generating the image () at the lowest resolution, then the generated image is scaled up to (()), and fed to the next level to generate an image (+ (())) at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.
Just after, the GAN game consists of the pair (() +), (() +) generating and discriminating 8x8 images. Here, the functions u , d {\displaystyle u,d} are image up- and down-sampling functions, and α {\displaystyle \alpha } is a blend-in factor (much like an alpha in image composing) that smoothly glides from 0 to 1.
The GAN uses a "generator" to create new images and a "discriminator" to decide which created images are considered successful. [32] Unlike previous algorithmic art that followed hand-coded rules, generative adversarial networks could learn a specific aesthetic by analyzing a dataset of example images.
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 ]
Users can use Midjourney through Discord either through their official Discord server, by directly messaging the bot, or by inviting the bot to a third-party server. To generate images, users use the /imagine command and type in a prompt; [23] the bot then returns a set of four images, which users are given the option to upscale. To generate ...
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]
Its production utilized advanced AI tools, including Runway Gen-3 Alpha and Kling 1.6, as described in the book Cinematic A.I. The book explores the limitations of text-to-video technology, the challenges of implementing it, and how image-to-video techniques were employed for many of the film's key shots.