Iterative working mechanism for deep research
The Deep Research feature of Deep Research Web UI is realized based on an intelligent iterative working mechanism. When a user enters a research topic, the system will first perform the first round of search and analysis, and then the AI will identify knowledge gaps based on the initial results and automatically generate more specific sub-problems to continue the search and analysis. This iterative process is repeated several times until comprehensive research results are obtained.
For example, when searching for "the application of artificial intelligence in the medical field", the system may obtain general information in the first round; in the second round, it will focus on "AI diagnostic technology"; and then it may be further refined to "the application of deep learning in imaging and diagnosis". The next round will focus on "AI diagnostic techniques"; the subsequent rounds may be further refined to "deep learning in imaging diagnosis". Each iteration will expand the depth and details of the research.
This feature is unique in that it completely automates this iterative process and visualizes the research path through a tree structure. This makes researching complex topics simple and efficient, while retaining the traceability and transparency of the research logic.
This answer comes from the articleDeep Research Web UI: an AI assistant supporting multilingual deep researchThe
