人与人社交，越界了要喊停。当AI扮演人，这样的"搭子"更加值得警惕。 国家互联网信息办公室近日发布通知，就《人工智能拟人化互动服务管理暂行办法（征求意见稿）》， 向社会公开征求意见。 监管新规瞄准的，是利用人工智能技术提供模拟人类人格特征、思维模式和沟通风格，并通过文字、图 片、音频、视频等方式与人类进行情感互动的产品或者服务。 "应当具备用户状态识别能力……发现用户存在极端情绪和沉迷的，采取必要措施予以干预""不得提供 模拟老年人用户亲属、特定关系人的服务""应当显著提示用户正在与人工智能而非自然人进行交 互"……新规在诸多细节化监管层面提出了要求。 这就是被俗称为AI"伴侣"或者AI"搭子"的新式服务。 说到底，AI"搭子"要有边界感，AI提供者要有敬畏心。 无论最火热的语言大模型，还是存在已久的聊天机器人，AI的发展目标都是越来越像人，除了作为生 产生活的工具（比如设计旅行方案、制作PPT等），AI在陪聊、咨询、陪伴等情感互动层面，也具备巨 大的创新和市场空间。 北京商报评论员 张绪旺 尤其在未成年人和老年人市场，情感互动类AI拥有比工具类AI更早一步的商业变现能力。甚至在年轻 人维度，也出现了"虚拟伴 ...

Core Viewpoint - The article discusses the ongoing competition in the AI industry regarding the development of long-term memory systems, highlighting different approaches taken by companies to enhance user experience and product differentiation in the AI landscape [1]. Group 1: From "Behavior Data" to "AI Memory" - Current AI products, such as assistants and virtual companions, primarily operate on a one-time interaction basis, which diminishes user trust and engagement [4]. - Long-term memory should be a core design element from the outset, rather than an afterthought, as emphasized by Artem Rodichev from Ex-human [4]. - Effective memory systems must balance the retention of significant events, updates based on user interactions, and user control over memory management [4]. - The true challenge in product differentiation lies not in replicating features but in how products learn and adapt through memory [4]. - Mainstream personal assistant systems categorize memory into short-term, mid-term, and long-term layers, enhancing understanding of user behavior over time [4]. - The interconnectedness of these memory layers creates a "behavioral compounding" effect, making it difficult for competitors to replicate this contextual depth [4]. - Companies are making strategic choices regarding what to remember, for whom, and for how long, aiming to establish a competitive edge through unique memory systems [4]. Group 2: Routes to Achieve AI's "Lifetime Memory" - Various product routes have emerged around AI long-term memory, each emphasizing different strategic narratives such as privacy, cost efficiency, speed, and integration [5].