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the article about bibliographic databases for information about databases giving bibliographic information about finding books and journal articles. The terms "free", "subscription", and "free & subscription" will refer to the availability of the website as well as the journal articles used.
Semantic Scholar is a research tool for scientific literature powered by artificial intelligence. It is developed at the Allen Institute for AI and was publicly released in November 2015. [ 2 ] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated ...
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 .
The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through the space of all possible hypotheses and yield the hypothesis - or set of equally likely hypotheses - that best describes the complex patterns in data.
Find this article at OpenDOAR, a search engine for academic repositories; Find this article in the DOAJ, a multidisciplinary index of open-access journal content; Find this article at CORE, an aggregator of open-access research; Find this article at PubMed Central, a medical database; Find this article in Paperity, a multidisciplinary ...
To help find sources, Wikipedians have developed a number of source-finding templates which link to searches most likely to find references suitable for use in articles. The most well-known of these is {{ find sources }} , an inline template which can be used almost anywhere.
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Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [ 1 ]
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