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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.
Generative AI systems such as MusicLM [56] and MusicGen [57] can also be trained on the audio waveforms of recorded music along with text annotations, in order to generate new musical samples based on text descriptions such as a calming violin melody backed by a distorted guitar riff.
Users will be able to generate videos up to 1080-pixel resolution up to 20 seconds long and in widescreen, vertical or square aspect ratios. OpenAI released its video-to-text model Sora Monday.
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 ]
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]
In the 2020s, text-to-image models, which generate images based on prompts, became widely used, marking yet another shift in the creation of AI generated artworks. [ 2 ] In 2021, using the influential large language generative pre-trained transformer models that are used in GPT-2 and GPT-3 , OpenAI released a series of images created with the ...
A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .
GPT-2 can generate thematically-appropriate text for a range of scenarios, even surreal ones like a CNN article about Donald Trump giving a speech praising the anime character Asuka Langley Soryu. Here, the tendency to generate nonsensical and repetitive text with increasing output length (even in the full 1.5B model) can be seen; in the second ...