Nature magazine tells us how Mushtaq Bilal is using a new generation of search engines, powered by machine learning and large language models, moving beyond keyword searches to pull connections from the mass of the scientific literature to speed up work. Some programs, such as Consensus, give research-backed answers to yes-or-no questions; others, such as Semantic Scholar, Elicit and Iris, act as digital assistants. Collectively, the platforms facilitate many of the early steps in the writing process. Critics note, however, that the programs remain relatively untested and run the risk of perpetuating existing biases in the academic publishing process. Can using AI free up time to allow more focus on innovation and discovery by drawing information from a massive body of literature and papers? Link below:
CAISS Bytes: A.I. Literature Reviews
