This text discusses the development of an autonomous dual-chatbot system for digesting research papers. The author explains that as a researcher, reading and understanding scientific papers is a crucial part of their daily routine. However, with the vast number of research papers being published, it becomes overwhelming to keep up with the latest trends and insights. The author highlights the recent development of large language models (LLMs) and how they can accurately identify relevant information from user-provided documents and generate high-quality answers. Despite the advancements, the author shares the friction points encountered when using existing document Q&A tools, such as the need for prompt engineering. As a result, the author proposes the idea of developing an automated system that can distill key points from research papers more efficiently and autonomously. The author draws inspiration from a previous project where a dual-chatbot system was developed for language learning and suggests that a similar approach could be useful for understanding research papers.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| Developing an Autonomous Dual-Chatbot System for Research Paper Digesting | Development of an automated Q&A system for research papers | More efficient and autonomous Q&A about research papers | Overwhelming amount of research papers being published daily |