Disrupt Your Research Using Generative AI Powered ScienceSage
Yong Zhang, Eric Herrison Gyamfi, Kelly Anderson, Sasha Roberts, Matt Barker
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- github.com/zhy5186612/GenAI-ResearchAssistant-ScienceSageOfficialnone★ 3
Abstract
Large Language Models (LLM) are disrupting science and research in different subjects and industries. Here we report a minimum-viable-product (MVP) web application called ScienceSage. It leverages generative artificial intelligence (GenAI) to help researchers disrupt the speed, magnitude and scope of product innovation. ScienceSage enables researchers to build, store, update and query a knowledge base (KB). A KB codifies user's knowledge/information of a given domain in both vector index and knowledge graph (KG) index for efficient information retrieval and query. The knowledge/information can be extracted from user's textual documents, images, videos, audios and/or the research reports generated based on a research question and the latest relevant information on internet. The same set of KBs interconnect three functions on ScienceSage: 'Generate Research Report', 'Chat With Your Documents' and 'Chat With Anything'. We share our learning to encourage discussion and improvement of GenAI's role in scientific research.