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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.
Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [ 3 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .
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]
Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [73] Google Photos, [74] and the Adobe Suite (Adobe Firefly). [75] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [76] language model.
QuarkXPress 8 introduced a completely new user interface, support for drag and drop, PDF 1.7 import, AI Import and a global file format. Design grids can be assigned to pages and boxes to allow unlimited baseline grids. Hanging characters can be applied and customized by character and amount to hang outside the box.
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AIMA gives detailed information about the working of algorithms in AI. The book's chapters span from classical AI topics like searching algorithms and first-order logic, propositional logic and probabilistic reasoning to advanced topics such as multi-agent systems, constraint satisfaction problems, optimization problems, artificial neural networks, deep learning, reinforcement learning, and ...
As an additional extension, mimicry-driven systems can be framed as agents who are optimizing a "goal function" based on how closely the IA succeeds in mimicking the desired behavior. [ 6 ] [ 2 ] In the generative adversarial networks of the 2010s, an "encoder"/"generator" component attempts to mimic and improvise human text composition.
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