Why Reinforcement Learning is the Future for AI Agents ft OpenAI’s Deep Research Team
Sequoia Capital
This podcast interviews Issa Fulford and Josh Tobin, leaders of OpenAI's Deep Research product, a new AI agent for comprehensive online research. The discussion covers Deep Research's capabilities, including its ability to generate detailed reports from web searches in minutes, surpassing human capabilities in speed and depth. The interview explores its development, using end-to-end reinforcement learning on hard browsing tasks, and its diverse applications, ranging from professional research to personal tasks like shopping and travel planning. Unexpected use cases, such as coding assistance, are highlighted, along with future development plans focusing on expanding data sources and integrating with other OpenAI agents. The discussion emphasizes the importance of end-to-end model training for creating powerful and flexible AI agents.
Part 1: Introduction to Deep Research
Part 2: Applications and Strengths
Part 3: Technical Deep Dive
Part 4: Future Outlook and Impact
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