用生成式AI打造政府智能助手，自动处理数据与报告
Exploring Generative AI Techniques in Government: A Case Study
- 构建智能代理Pubbie，用LLM与语义嵌入实现任务自动化
- 22个试点项目中，用户可通过自然语言操作，一键上传下载文件
- 低成本微调+少样本学习，让专业能力快速适配政府场景
生成式人工智能（GenAI），尤其是大语言模型（LLMs），正迅速重塑数字生态。为把握其变革潜力，加拿大国家研究委员会（NRC）于2024年5月启动22个试点项目，探索将GenAI技术融入日常运营以提升绩效。本文以其中开发的智能代理Pubbie为例，旨在实现NRC层面的绩效评估、数据管理与洞察报告自动化。研究采用先进的LLM编排与基于RoBERTa的语义嵌入技术，结合策略性微调和少样本学习方法，在较低成本下注入领域知识。Pubbie提供友好的用户界面，支持政府普通用户以自然语言提问，并通过一键按钮轻松上传或下载文件，显著降低人工负担与使用门槛。
原文摘要 · Abstract (English)
The swift progress of Generative Artificial intelligence (GenAI), notably Large Language Models (LLMs), is reshaping the digital landscape. Recognizing this transformative potential, the National Research Council of Canada (NRC) launched a pilot initiative to explore the integration of GenAI techniques into its daily operation for performance excellence, where 22 projects were launched in May 2024. Within these projects, this paper presents the development of the intelligent agent Pubbie as a case study, targeting the automation of performance measurement, data management and insight reporting at the NRC. Cutting-edge techniques are explored, including LLM orchestration and semantic embedding via RoBERTa, while strategic fine-tuning and few-shot learning approaches are incorporated to infuse domain knowledge at an affordable cost. The user-friendly interface of Pubbie allows general government users to input queries in natural language and easily upload or download files with a simple button click, greatly reducing manual efforts and accessibility barriers.
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