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Deep Research System Card
Overview :
Deep Research is a new model capability developed by OpenAI, focusing on conducting multi-step, complex research via the internet. Optimized from earlier versions of OpenAI's o3, it can search, interpret, and analyze large volumes of text, images, and PDF files, flexibly adapting its strategy based on encountered information. The model can also read user-provided files and analyze data by writing and executing Python code. Key advantages include powerful reasoning capabilities and efficient handling of complex tasks, making it suitable for scenarios requiring in-depth research and analysis. It's rooted in OpenAI's ongoing innovation in artificial intelligence, aiming to provide users with more powerful tools to solve complex real-world problems. Currently, the model is primarily aimed at Pro users, with pricing and specific positioning yet to be defined.
Target Users :
This product is designed for professionals who need to conduct complex information retrieval and analysis, such as researchers, analysts, and data scientists. It helps them efficiently complete multi-step research tasks, saving time and effort.
Use Cases
Researchers use Deep Research to retrieve and analyze large amounts of academic literature, quickly identifying key information.
Data analysts utilize the model to analyze internet data and generate valuable reports.
Enterprise users leverage Deep Research to search for market information and develop business strategies.
Features
Multi-step, complex internet research capability
Ability to search, interpret, and analyze large volumes of text, images, and PDF files
Flexible adaptation of research strategy based on encountered information
Reading and analyzing user-provided files
Data processing through writing and executing Python code
Enhanced privacy protection to prevent personal information leakage
Resistance to malicious instructions to ensure the security of the search process
How to Use
1. Register and log in to the OpenAI platform and select the Deep Research function.
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2. Provide the research topic or task; the model will automatically initiate multi-step research.
3. The model searches the internet for relevant information and performs inferential analysis.
4. Provide additional files or data as needed; the model will read and integrate the analysis.
5. Review the research results and analytical reports generated by the model.
6. If necessary, further adjust research parameters or optimize task instructions.
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