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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 ...
Authorea allows researchers to write documents together and attach references, figures, data, and source code. Features of the tool include collaborative editing (multiple people editing a document at the same time), automatic citation formatting, tracking changes, and the ability to make any document public or fully private.
The Research Brief is a short take about interesting academic work. The big ideaThe scientific community worldwide has mobilized with unprecedented speed to tackle the COVID-19 pandemic, and the ...
Writing review articles, for example, is a task well suited to AI: it involves sifting through the existing research on a subject, analyzing the results, reaching a conclusion about the state of ...
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 ...
Pre-prints, mainly computer science, mathematics, statistics, chemistry, and biology. Free Yes Synthical Zendy [22] Multidisciplinary: Unknown (31,266,280 [23] Focus on scholarly content including full-text papers, conference proceedings, indexed journals, books, and book chapters from open access sources. Content is available in 38 languages ...
DeepMind is known to have trained the program on over 170,000 proteins from the Protein Data Bank, a public repository of protein sequences and structures.The program uses a form of attention network, a deep learning technique that focuses on having the AI identify parts of a larger problem, then piece it together to obtain the overall solution. [2]
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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