Core Viewpoint - The article discusses the advancements in the Agent technology landscape, highlighting the integration of Baidu's AI search capabilities into the Baidu Intelligent Cloud Qianfan platform, which addresses the limitations of real-time information access and enhances the overall functionality of Agents [1][2][3]. Group 1: Agent Technology Development - The transition of Agents from handling simple tasks to managing complex deliveries is noted, yet they still face challenges due to "information gaps" caused by outdated training data [1]. - Baidu's AI search capability is now available through the Qianfan platform, allowing Agents to access real-time data and diverse information sources, thereby improving the authority and accuracy of the output [2][3][10]. - The integration of AI search with Agents emphasizes comprehensive, authoritative, and timely results, which can reduce model hallucinations and assist in generating training data for various applications [10][11]. Group 2: Qianfan 4.0 Enhancements - Qianfan 4.0 is positioned as the most comprehensive enterprise-level AI platform, featuring upgrades in core capabilities, including data services and enhanced Agent services [4][5]. - The platform has aggregated over 150 selected model services, including Baidu's self-developed models and industry-specific models, allowing enterprises to access cutting-edge technology [5][27]. - Key elements for building enterprise-level Agents include a robust orchestration framework, a comprehensive toolset, continuous model iteration, and a secure operational environment [12][26]. Group 3: Multi-Modal RAG and Knowledge Graph Integration - The introduction of multi-modal RAG enhances the ability to analyze complex internal data, significantly improving parsing efficiency for various document types [15]. - The integration of knowledge graphs with RAG expands the recall range and improves retrieval accuracy in applications such as risk control and marketing [16][17]. - This combination allows Agents to access both external and internal information, marking a significant leap in their information acquisition capabilities [17]. Group 4: Collaboration and Ecosystem Development - Qianfan 4.0 supports multi-agent collaboration, where a "planner" agent breaks down tasks and assigns them to "executor" agents, maximizing tool efficiency [18][19]. - The platform's extensibility allows for the dynamic introduction of new Agents based on existing functionalities, enhancing operational flexibility [19]. - Baidu plans to open more exclusive technologies as MCP Servers, fostering a collaborative ecosystem among developers and third-party services [21][22]. Group 5: Model and Data Management - Qianfan 4.0 standardizes the four essential components for deploying Agents: models, toolchains, data, and operational guarantees [26]. - The platform facilitates seamless integration of high-quality models and provides tools for scenario-based tuning and rapid evaluation, enhancing the adaptability of Agents [27][30]. - A new data intelligence service platform addresses enterprise data governance challenges, covering the entire lifecycle of data management and accelerating model iteration [36][38]. Group 6: Market Position and Future Outlook - Baidu Intelligent Cloud holds a 14.9% market share in the large model platform market, maintaining its position as an industry leader [42]. - The strategic approach focuses on building a robust infrastructure for Agents rather than merely creating demonstration-level Agents, emphasizing the aggregation of capabilities into a cohesive network [41][42]. - The shift from a "model competition" to a "platform and infrastructure competition" signifies a broader evolution in the industry, allowing businesses to leverage Qianfan as a foundational base for continuous improvement [43].

据沈抖介绍，百度最新发布的视频生成模型蒸汽机2.0，以及十余款垂直行业模型，均已集成到千帆大 模型上。此外，百度还发布了RFT工具链，通过提供奖励模型，可以让RFT训练效率提升43%。（文 猛） 责任编辑：李芊蔚 新浪科技讯 8月28日上午消息，今日举办的2025百度云智大会上，百度集团执行副总裁、百度智能云事 业群总裁沈抖宣布，百度智能云千帆4.0发布，精选150+模型服务，能够让用户第一时间用上SOTA模 型。 ...