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arXiv · 2502.18479

Disrupt Your Research Using Generative AI Powered ScienceSage

Yong Zhang·Eric Herrison Gyamfi·Kelly Anderson·Sasha Roberts·Matt Barker
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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 $\textbf{ScienceSage}$. It leverages generative artificial intelligence (GenAI) to help researchers disrupt the speed, magnitude and scope of product innovation. $\textbf{ScienceSage}$ 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 $\textbf{ScienceSage}$: '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.

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Yong Zhang, Eric Herrison Gyamfi, Kelly Anderson, Sasha Roberts, Matt Barker. 2025-02-06. Disrupt Your Research Using Generative AI Powered ScienceSage. https://arxiv.org/abs/2502.18479

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