Core Insights - The article emphasizes the importance of understanding that intelligent agents are not a one-size-fits-all solution but require a long-term, systematic engineering approach [2][3] - McKinsey's research on 50 real projects indicates that companies often fall into similar traps when developing intelligent agents, such as over-reliance on single-point demos and neglecting engineering and governance [2] - Gartner predicts that by 2027, over 40% of Agentic AI projects will be abandoned due to imbalances in cost, value, and engineering implementation [2] Event Overview - The 2025 Global Machine Learning Technology Conference will feature a special topic on "Intelligent Agent Engineering and Practice," gathering top scholars and industry practitioners to address core pain points in the implementation of intelligent agents [3][6] - The conference will include notable speakers such as former OpenAI researcher Wu Yi and algorithm scientists from various leading tech companies, sharing their latest research and practical experiences in the field of intelligent agents [6][28] - The event aims to provide attendees with a comprehensive understanding of the engineering methods and practical experiences related to intelligent agents in the era of large models [6][28] Registration and Participation - The registration for the conference is closing soon, emphasizing the urgency for interested participants to secure their spots [28][29] - The conference has become an annual gathering for thousands of AI professionals since its inception in 2017, highlighting its significance in the AI community [28]

Core Insights - The article emphasizes the transition of AI from impressive demos to a rigorous focus on architecture, systems, data, and business integration, highlighting the need for sustainable industrial capabilities [1] - The 2025 Global Machine Learning Technology Summit, organized by CSDN and Singularity Research Institute, will take place on October 16-17 in Beijing, featuring over 50 prominent speakers from academia and industry [1][3] Group 1: Event Overview - The summit aims to address the pressing question of how to transform technological breakthroughs into sustainable industrial capabilities [1] - A comprehensive "full-stack battle map" of AI has been designed, featuring 12 core topics including the evolution of large language models, AI-enabled software development, and practical applications of large models [3][4] Group 2: Key Speakers and Topics - Zhao Jian will discuss AI safety and governance, focusing on the security risks and ethical challenges of large models, along with innovative governance solutions [5][8] - Zhou Pan will present the MindGPT-4o-Audio, a real-time voice dialogue model that achieves human-like interaction capabilities [11][14] - Leng Dawei will share insights on FG-CLIP, a high-precision image-text alignment model designed for large-scale applications [16][19] - Zhang Heng will explore the transition from academic research to commercial AI visual algorithms, detailing the development process from prototypes to products [20][24] - Zhang Jun will introduce the Wenxin 4.5 open-source model and its key training technologies, addressing challenges in model training and inference [25][29] - Zhang Dao Xin will discuss the application of multimodal models in Xiaohongshu's search functionalities, focusing on content understanding and retrieval systems [30][33] - Han Ai will present the OxyGent framework for multi-agent collaboration in JD Retail, emphasizing its modular design for flexible system development [34][37] - Wang Peiyu will cover advancements in multimodal reasoning and unified models, showcasing the evolution of the r1v series [39][42] - Cui Cheng will discuss the latest technologies in PaddleOCR and its applications in various industries [43][46] - Xiao Chaojun will introduce MiniCPM, an efficient model for edge devices, highlighting breakthroughs in architecture and training algorithms [47][49] - Chen Yingfeng will explore the application of embodied intelligence in engineering machinery, focusing on human-robot collaboration [50][53] - Zhang Shaobo will present the LLM Agent's role in software engineering, demonstrating its capabilities in solving real development challenges [54][57] - Zhang Dan will discuss how AI large models can help overcome challenges in L4 autonomous driving, sharing insights on commercial applications [58][61] - Han Zongbo will address uncertainty modeling in AI, providing a framework for enhancing reliability in complex scenarios [62][65] Group 3: Future Directions - The summit serves as a platform for deep exchanges in AI technology, fostering collaboration and innovation across industries [74] - The event aims to capture cutting-edge trends and explore pathways for industrial upgrades, inviting global AI participants to engage in discussions [74]