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e. A large language model (LLM) is a computational model capable of language generation or other natural language processing tasks. As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.
v. t. e. Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]
e. DALL·E, DALL·E 2, and DALL·E 3 (pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] [18] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
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 September 2024 it is unreleased and not yet available to the public.
Text-to-image model. An image conditioned on the prompt "an astronaut riding a horse, by Hiroshige ", generated by Stable Diffusion, a large-scale text-to-image model released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
Zalgo text. Zalgo text, also known as cursed text or glitch text due to the nature of its use, is digital text that has been modified with numerous combining characters, Unicode symbols used to add diacritics above or below letters, to appear frightening or glitchy. Named for a 2004 Internet creepypasta story that ascribes it to the influence ...
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.