NVIDIA has just rolled out the Universal Deep Research (UDR) system. This system not only allows for personalized customization tailored to individual users' needs but also boasts seamless connectivity with any Large Language Model (LLM). In the past, traditional deep research agents predominantly depended on hardcoding techniques. This approach severely restricted the degree of customization available to users and led to poor practicality in real-world scenarios. In stark contrast, the UDR system presents a versatile and all-encompassing solution.

Among its standout features, the UDR system enables users to customize research strategies effortlessly through natural language. It adopts a model-agnostic architecture for research tools, ensuring compatibility with a wide range of models. Additionally, it provides a research interface driven by user-controllable strategies, enhancing the user's ability to steer the research process. On top of that, the system is designed to boost computational efficiency and drive down costs.

However, it's important to note that the UDR system currently has a few limitations. For instance, the accuracy of the execution strategies can be affected by the quality of the code in the underlying model. Moreover, the default strategies need to be both reasonable and effective to ensure optimal performance. Another drawback is the lack of support for user intervention during the execution phase. Researchers are actively working on formulating improvement plans to address these issues. At present, the UDR system is still in its prototype stage, and we eagerly await the launch of its official version.