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  2. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  3. Text-to-video model - Wikipedia

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

    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 .

  4. Hypervideo - Wikipedia

    en.wikipedia.org/wiki/Hypervideo

    Text is normally static, while a video is dynamic; the content of the video changes with time. Consequently, hypervideo has different technical, aesthetic, and rhetorical requirements than a static hypertext page. For example, hypervideo might involve the creation of a link from an object in a video that is visible for only a certain duration.

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

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

    Sora is a text-to-video model developed by OpenAI. The model generates short video clips based on user prompts, and can also extend existing short videos. Sora was released publicly for ChatGPT Plus and ChatGPT Pro users in December 2024. [1] [2]

  6. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Embedding vectors created using the Word2vec algorithm have some advantages compared to earlier algorithms [1] such as those using n-grams and latent semantic analysis. GloVe was developed by a team at Stanford specifically as a competitor, and the original paper noted multiple improvements of GloVe over word2vec. [ 9 ]

  7. Sentence embedding - Wikipedia

    en.wikipedia.org/wiki/Sentence_embedding

    In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.

  8. Dream Machine (text-to-video model) - Wikipedia

    en.wikipedia.org/wiki/Dream_Machine_(text-to...

    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]

  9. Help:Creation and usage of media files - Wikipedia

    en.wikipedia.org/wiki/Help:Creation_and_usage_of...

    File – To create a link to the video's File Description Page, use [[:File:Time Lapse of New York City.ogv]]. To make the text of a link to the video's File Description Page appear as some text other than the video's filename, use [[:File:Time Lapse of New York City.ogv|some text you prefer]]. Media – To create a link that downloads the video,