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deepmind.google·6d ago
AI Engineering
OpenAI Blog·Apr 10·5 min read
Research with ChatGPT
TL;DR
Researchers and practitioners often struggle to verify information currency and synthesize insights from multiple sources when using language models. OpenAI built search and deep research capabilities into ChatGPT, enabling users to retrieve up-to-date information, evaluate source credibility, and organize findings into structured outputs.
✦ Why It Matters
Engineers can now use ChatGPT for fact-checked research with cited sources, reducing manual verification overhead and improving decision confidence.
Key Takeaways
- Use ChatGPT search mode to retrieve real-time web results for current information needs.
- Leverage deep research mode for complex topics requiring multi-source synthesis and analysis.
- Request structured outputs with citations to validate findings and trace information sources.
- Integrate ChatGPT research into workflows to reduce time spent on manual source discovery.
Full Summary
Finding and synthesizing current information from multiple sources remains time-consuming for engineers and researchers. OpenAI integrated two research modes into ChatGPT: search functionality that retrieves real-time web results, and deep research mode that autonomously explores topics across multiple sources and synthesizes findings into coherent reports.
The search feature pulls live data from the internet, while deep research uses iterative querying and source analysis to build comprehensive understanding. Users can now ask ChatGPT complex research questions and receive structured outputs with cited sources rather than fragmented results.
This approach reduces manual research overhead by automating source discovery, relevance filtering, and synthesis. The capability enables faster literature reviews, competitive analysis, and technical investigation workflows.
Engineers can now validate assumptions and gather context more efficiently before implementation.