用生成式AI构建科研知识库，加速研究创新
Disrupt Your Research Using Generative AI Powered ScienceSage
- 将文本、图像等多模态数据构建成向量与知识图谱双索引知识库
- 支持生成报告、文档对话和任意内容问答三大功能联动
- 适合希望提升研究效率的科研人员快速上手使用
大型语言模型正在重塑科学与研究领域。本文介绍一个最小可行产品（MVP）网页应用——ScienceSage，该系统利用生成式人工智能（GenAI）助力研究人员加速产品创新的速度、规模与范围。ScienceSage可帮助研究者构建、存储、更新并查询知识库（KB），将特定领域的知识以向量索引和知识图谱（KG）索引形式编码，实现高效的信息检索与查询。知识来源包括用户上传的文本、图像、视频、音频，以及基于研究问题和互联网最新相关信息生成的研究报告。同一套知识库联动支持三项核心功能：生成研究报告、与文档对话、与任何内容对话。我们分享实践经验，旨在推动生成式AI在科学研究中的讨论与优化。
原文摘要 · Abstract (English)
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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