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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 ...
Question answering systems in the context of [vague] machine reading applications have also been constructed in the medical domain, for instance related to [vague] Alzheimer's disease. [3] Open-domain question answering deals with questions about nearly anything and can only rely on general ontologies and world knowledge. Systems designed for ...
The Stanford Institute for Human-Centered Artificial Intelligence's (HAI) Center for Research on Foundation Models (CRFM) coined the term "foundation model" in August 2021 [16] to mean "any model that is trained on broad data (generally using self-supervision at scale) that can be adapted (e.g., fine-tuned) to a wide range of downstream tasks". [17]
Artificial intelligence is used in astronomy to analyze increasing amounts of available data [159] [160] and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" for example for discovering exoplanets, forecasting solar activity, and distinguishing ...
The high-level architecture of IBM's DeepQA used in Watson [9]. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.
AI leaders are rethinking the conventional wisdom about how to train large language models. ... This is the biggest question in AI right now. Lakshmi Varanasi,Lloyd Lee. November 24, 2024 at 12:08 ...