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Google researchers have developed a new framework for AI research agents that outperforms leading systems from rivals OpenAI, Perplexity, and others on key benchmarks.
The new agent, called Test-Time Diffusion Deep Researcher (TTD-DR), is inspired by the way humans write by going through a process of drafting, searching for information, and making iterative revisions.
The system uses diffusion mechanisms and evolutionary algorithms to produce more comprehensive and accurate research on complex topics.
For enterprises, this framework could power a new generation of bespoke research assistants for high-value tasks that standard retrieval augmented generation (RAG) systems struggle with, such as generating a competitive analysis or a market entry report.
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According to the paper’s authors, these real-world business use cases were the primary target for the system.
The limits of current deep research agents
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