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Sora is an up and coming generative artificial intelligence model developed by OpenAI, that specializes in text-to-video generation. The model generates short video clips corresponding to prompts from users. Sora can also extend existing short videos. As of October 2024 it is unreleased and not yet available to the public.
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. [166] Training an AI model exclusively on the output of another AI model produces a lower-quality model.
DALL·E, DALL·E 2, and DALL·E 3 (pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
Dream Machine is a text-to-video model created by the San Francisco-based generative artificial intelligence company Luma Labs, which had previously created Genie, a 3D model generator. It was released to the public on June 12, 2024, which was announced by the company in a post on X alongside examples of videos it created. [1]
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. [1] [2] It is one of the technologies of ...
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. In 2022, the output of state-of-the-art text-to ...
Artificial intelligence. Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The model is capable of generating legible text in the images compared to other text-to-image models. [1][2]
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. [1][2] The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. [3] In a GAN, two neural networks contest with each other in the form of a zero-sum game ...
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