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Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Reading scientific papers is a tough job. Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and ...
Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.
Apple’s new iPhone 16 lineup features new colors, a new camera button and – perhaps most noteworthy – a new artificial intelligence system.. The tech giant is set to roll out features from ...
On December 23, 2022, You.com was the first search engine to launch a ChatGPT-style chatbot with live web results alongside its responses. [25] [26] [12] Initially known as YouChat, [27] the chatbot was primarily based on the GPT-3.5 large language model and could answer questions, suggest ideas, [28] translate text, [29] summarize articles, compose emails, and write code snippets, while ...
The artificial intelligence firm said the threat actors used its AI models to generate short comments, longer articles in a range of languages, made up names and bios for social media accounts ...
These classes are independent of a specific modeling architecture such as Transformer, but they are often discussed in the context of Transformer. In a masked task, [ 49 ] one or more of the tokens is masked out, and the model would produce a probability distribution predicting what the masked-out tokens are based on the context.