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  2. Text-to-video model - Wikipedia

    en.wikipedia.org/wiki/Text-to-Video_model

    Many pedestrians walk about. A text-to-video model is a machine learning model that takes a natural language description as input and produces a video relevant to the input text. [1] Recent advancements in generating high-quality, text-conditioned videos have largely been driven by the development of video diffusion models.

  3. Sora (text-to-video model) - Wikipedia

    en.wikipedia.org/wiki/Sora_(text-to-video_model)

    Sora is an upcoming 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 August 2024 it is unreleased and not yet available to the public.

  4. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". [1] Text is converted to numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. [1]

  5. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion. Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom .

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning ), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine ...

  7. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is enabled by in-context learning, defined as a model's ability to temporarily learn from prompts. The ability for in-context learning is an emergent ability [14] of large language models. In-context learning itself is an emergent property of model scale, meaning breaks [15] in downstream scaling laws occur such that its ...

  8. Category:Text-to-video generation - Wikipedia

    en.wikipedia.org/wiki/Category:Text-to-video...

    Sora (text-to-video model) Categories: Language modeling. Machine learning task. Deep learning. Computer graphics. Artificial intelligence art. Video processing. Film and video technology.

  9. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    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 ...