五位AI企业负责人直面核心矛盾。 在AI加速渗透各行各业的今天，AI Agent已从炙手可热的概念，迈向价值验证的关键十字路口。它究竟是企业降本增效的利器，还是驱动增长的新引擎？ 在落地过程中，又面临哪些信任、成本与习惯的深层阻力？ 12月3日下午，在2025甲子引力年终盛典中，甲子光年智库院长宋涛作为主持人，对话卓世科技创始合伙人&COO李伟伟、红熊AICEO温德亮、深度原理 COO张露阳、蚂蚁数科AI原生科技总经理王磊、零一万物企业解决方案技术负责人王猛，围绕《智能体社会：人与AI共创的产业秩序》这一主题展开了 深入探讨。 这些观点共同揭示了一个趋势：AI Agent的价值正从技术能力转向真实的商业产出——它必须深入业务，解决问题，并交出可衡量的价值答卷。 以下为本场圆桌的文字实录，经「甲子光年」编辑，在不改变原意的基础上略有删改。 宋涛（主持人）：感谢各位嘉宾的到来，先请各位嘉宾简单的用一句话做自我介绍，介绍一下个人和你们的公司。 王猛（零一万物企业解决方案技术负责人）：我在大模型独角兽公司零一万物在负责打造万智企业大模型一站式平台，这是一款端到端的平台型产品，覆 盖从模型训练、工具链构建到应用开发的全 ...

Core Viewpoint - The article discusses the limitations of large models in retaining long-term memory, highlighting the challenges faced in practical applications and the need for a more human-like memory system in AI [3][10][25]. Group 1: Limitations of Current AI Models - The large model industry is experiencing a "memory loss" issue, where AI struggles to retain information over extended interactions, leading to repeated questions and irrelevant responses [4][6]. - The technical architecture of current models, such as the Transformer, suffers from attention decay over long sequences, resulting in the loss of earlier instructions during conversations [5][7]. - The lack of a shared memory mechanism among different AI agents leads to fragmented interactions, causing inefficiencies and confusion in customer service scenarios [6][7]. Group 2: Need for Improved Memory Mechanisms - A more sophisticated memory system is essential for AI to evolve beyond simple question-answering capabilities and to develop understanding and reasoning abilities [15][26]. - The concept of memory in AI should not just focus on storing more data but on retaining valuable information that can guide decision-making [11][12]. - The development of a memory infrastructure that allows for shared, manageable, and traceable memory among AI agents is crucial for enhancing their collaborative capabilities [10][22]. Group 3: Redefining AI Memory with "Memory Bear" - The company "Red Bear AI" is working on a product called "Memory Bear," which aims to create a memory system that mimics human memory processes, allowing for better retention and utilization of information [10][28]. - This system includes short-term working memory for task connections and long-term memory for knowledge retention, enabling AI to respond more accurately and contextually [14][18]. - The introduction of a structured memory graph allows for the analysis and retrieval of relevant memories, significantly improving the efficiency and accuracy of AI responses [17][18]. Group 4: Implications for Business and Future of AI - The ability of AI to retain memory will fundamentally change its role in business, allowing it to replace human-like interactions in customer service and other sectors [21][22]. - As AI develops a continuous memory, it will be able to understand user context and history, enhancing trust and effectiveness in various applications [22][26]. - The evolution of memory systems in AI is seen as a critical step towards achieving general artificial intelligence (AGI), where memory plays a vital role in reasoning and learning [26][28].