用大模型对话专家，让搜索从查资料升级为深度交流
Musings About the Future of Search: A Return to the Past?
- 用大语言模型模拟专家对话，替代传统静态信息检索
- 用户可直接提问并获得动态交互式回答，提升信息获取效率
- 适合希望深度理解复杂问题的研究者与专业人士
当有疑问时，最有效的解决方式是直接与领域专家对话。在文字发明前，这唯一可行的途径。虽然有效，但难以规模化。文字使知识得以固化、保存和复制，推动了各类技术发展，最终形成我们熟悉的十蓝链接网页搜索模式。然而，静态内容消费始终存在局限。随着大语言模型的出现，用户可直接与虚拟专家互动，不仅满足信息需求，还能实现深度交流与推理。这一未来需要重新构想搜索的本质。
原文摘要 · Abstract (English)
When you have a question, the most effective way to have the question answered is to directly connect with experts on the topic and have a conversation with them. Prior to the invention of writing, this was the only way. Although effective, this solution exhibits scalability challenges. Writing allowed knowledge to be materialized, preserved, and replicated, enabling the development of different technologies over the centuries to connect information seekers with relevant information. This progression ultimately culminated in the ten-blue-links web search paradigm we're familiar with, just before the recent emergence of generative AI. However, we often forget that consuming static content is an imperfect solution. With the advent of large language models, it has become possible to develop a superior experience by allowing users to directly engage with experts. These interactions can of course satisfy information needs, but expert models can do so much more. This coming future requires reimagining search.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。