关于大模型落地，腾讯给了两个方向：智能体和知识库

Core Insights - The development of practical and efficient AI agents is a significant challenge for the industry, as highlighted by Tencent's focus on creating products that address real business needs [2][3] - Tencent emphasizes the importance of user experience in AI agent development, ensuring that agents not only provide answers but also take responsibility for those answers in real business scenarios [3] Group 1: AI Agent Development - Key considerations in AI agent design include intelligent rollback, document comparison, and reinforcement of Q&A pairs to enhance accuracy and usability [2][4] - The essence of AI agents in B2B scenarios is their ability to autonomously plan and execute tasks based on natural language instructions, distinguishing them from traditional software [5] - Tencent's QQ browser has been upgraded to an AI browser with the introduction of QBot, indicating a shift towards AI integration in traditional browsing experiences [5][6] Group 2: Knowledge Base Integration - The combination of AI agents with enterprise knowledge bases is seen as a critical need, enhancing the precision of decision-making and execution in businesses [8][9] - Tencent's LeXiang has been upgraded to serve as a knowledge management tool, integrating with large models to improve knowledge flow and efficiency [10] - The evolution of large models has significantly improved language understanding capabilities, allowing for better integration of AI technologies into business processes [11]