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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]
The CLIP models released by OpenAI were trained on a dataset called "WebImageText" (WIT) containing 400 million pairs of images and their corresponding captions scraped from the internet. The total number of words in this dataset is similar in scale to the WebText dataset used for training GPT-2, which contains about 40 gigabytes of text data. [1]
According to Warner Bros. Discovery, the “Caption AI” workflow reduces caption file creation time up to 80% compared with manual captioning and cuts captioning costs by up to 50%.
Captions is a video-editing and AI research company headquartered in New York City. Their flagship app, Captions , is available on iOS , Android , and Web and offers a suite of tools aimed at streamlining the creation and editing of videos.
OpenAI and non-profit partner Common Sense Media have launched a free training course for teachers aimed at demystifying artificial intelligence and prompt engineering, the organizations said on ...
Seq2seq RNN encoder-decoder with attention mechanism, training Seq2seq RNN encoder-decoder with attention mechanism, training and inferring The attention mechanism is an enhancement introduced by Bahdanau et al. in 2014 to address limitations in the basic Seq2Seq architecture where a longer input sequence results in the hidden state output of ...