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A 2016 research project called "One Hundred Year Study on Artificial Intelligence" named Wikipedia as a key early project for understanding the interplay between artificial intelligence applications and human engagement. [30] There is a concern about the lack of attribution to Wikipedia articles in large-language models like ChatGPT. [19]
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 ...
Identifying AI-assisted edits is difficult in most cases since the generated text is often indistinguishable from human text. Some exceptions are if the text contains phrases like "as an AI model" or "as of my last knowledge update" and if the editor copy-pasted the prompt used to generate the text together with the AI response.
Lex Fridman (/ ˈ f r iː d m ə n /; born 15 August 1983) [2] is an American computer scientist and podcaster.Since 2018, he has hosted the Lex Fridman Podcast, where he interviews notable figures from various fields such as science, technology, sports, and politics.
As an example, a project highlighting intelligence in the domain model may generate solutions to complex and novel problems so that students can always have new problems to work on, but it might only have simple methods for teaching those problems, while a system that concentrates on multiple or novel ways of teaching a particular topic might ...
Google CEO Sundar Pichai and other top executives at the tech giant closed out the year with a meeting earlier this month that sought to tee up 2025, which they view as a pivotal year, especially ...
Caselaw Access Project All official, book-published state and federal United States case law — every volume or case designated as an official report of decisions by a court within the United States.
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.