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Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
In March 2023, Quizlet started to incorporate AI features with the release "Q-Chat", a virtual AI tutor powered by OpenAI's ChatGPT API. [24] [25] [26] Quizlet launched four additional AI powered features in August 2023 to assist with student learning. [27] [28] In July 2024, Kurt Beidler, the former co-CEO of Zwift, joined Quizlet as the new ...
ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]
Brainly is an education company based in Kraków, Poland, with headquarters in New York City.It is an AI-powered homework help platform targeting students and parents. As of November 2020, Brainly reported having 15 million daily active users, making it the world's most popular education app. [2] In 2024, FlexOS reported Brainly as the #1 Generative AI Tool in the education category and the #6 ...
GPT-2's flexibility was described as "impressive" by The Verge; specifically, its ability to translate text between languages, summarize long articles, and answer trivia questions were noted. [ 17 ] A study by the University of Amsterdam employing a modified Turing test found that at least in some scenarios, participants were unable to ...
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. [ 1 ]
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] 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.
In linguistics, transformational grammar (TG) or transformational-generative grammar (TGG) was the earliest model of grammar proposed within the research tradition of generative grammar. [1] Like current generative theories, it treated grammar as a system of formal rules that generate all and only grammatical sentences of a given language.