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Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative artificial intelligence (AI) model. [ 1 ] [ 2 ] A prompt is natural language text describing the task that an AI should perform. [ 3 ]
A human performs prompt engineering when they write a prompt. An AI performs in-context learning when it reads the prompt, understands it, and correctly responds. If you are an office worker and you want to know how to prompt GPT-4 to do your work for you, then you want an article about prompt engineering with practical information and lots of ...
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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 ]
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Obtaining a certificate is voluntary in some fields, but in others, certification from a government-accredited agency may be legally required to perform certain jobs or tasks. Organizations in the United States involved in setting standards for certification include the American National Standards Institute (ANSI) and the Institute for ...
While OpenAI did not release the fully-trained model or the corpora it was trained on, description of their methods in prior publications (and the free availability of underlying technology) made it possible for GPT-2 to be replicated by others as free software; one such replication, OpenGPT-2, was released in August 2019, in conjunction with a ...
There are several architectures that have been used to create Text-to-Video models. Similar to Text-to-Image models, these models can be trained using Recurrent Neural Networks (RNNs) such as long short-term memory (LSTM) networks, which has been used for Pixel Transformation Models and Stochastic Video Generation Models, which aid in consistency and realism respectively. [31]