喝点VC｜红杉对谈OpenAI Agent团队：将Deep Research与Operator整合成主动为你做事的最强Agent

Core Insights - The article discusses the integration of OpenAI's Deep Research and Operator projects to create a powerful AI Agent capable of executing complex tasks for up to one hour [2][5][6] - The AI Agent utilizes a virtual computer with various tools, including a text browser, GUI browser, terminal access, and API calling capabilities, allowing it to perform tasks that typically require human effort [6][7][24] - The model is designed to facilitate user interaction, enabling users to interrupt, correct, and clarify tasks during execution, which enhances its flexibility and effectiveness [7][22] Integration of Deep Research and Operator - The combination of Deep Research and Operator leverages the strengths of both projects, with Operator excelling in visual interactions and Deep Research in text-based information processing [9][10] - The integration allows the AI Agent to access paid content and perform tasks that require both browsing and interaction with web elements [10][11] - The collaboration has resulted in a more versatile toolset, enabling the AI Agent to perform a wider range of tasks, including generating reports, making purchases, and creating presentations [11][14] Real-World Applications - The AI Agent is designed for both consumer and professional use, targeting "prosumer" users who are willing to wait for detailed reports [15] - Examples of its application include data extraction from spreadsheets, online shopping, and generating financial models based on web-sourced information [16][18] - The model's ability to handle complex tasks autonomously is highlighted, with a recent task taking 28 minutes to complete, showcasing its potential for longer, more intricate assignments [19][20] Training and Development - The AI Agent is trained using reinforcement learning, where it learns to use various tools effectively by completing tasks that require their use [24][25] - The training process involves a significant increase in computational resources and data, allowing for more sophisticated model capabilities [45] - The development team emphasizes the importance of collaboration between research and application teams to ensure the model meets user needs from the outset [30][35] Future Directions - OpenAI aims to enhance the AI Agent's capabilities further, focusing on improving accuracy and performance across diverse tasks [37][49] - The potential for new interaction paradigms between users and the AI Agent is anticipated, with the goal of making the Agent more proactive in assisting users [49][42] - The team is excited about the ongoing exploration of the Agent's capabilities and the discovery of new use cases as it evolves [40][49]