吃饱了，咱们继续聊点真的问题！ 锦秋小饭桌一个锦秋基金的固定"活动"，每周五晚在北京、深圳、上海、杭州等地举办的AI创业者闭门社交活动。我们把最优秀的创业者、技术大牛、产品创新者 聚在一起，围着一桌好菜，聊那些在办公室里不会聊的真话——没有PPT轰炸，没有商业互吹，只有实打实的干货分享和真诚交流，可能还有各种不敢跟人分享的 创业艰难时刻和投资的决策逻辑。 从2月底第一顿饭开始，不知不觉我们已经连续举办了28场。如果你错过了之前的精彩，没关系——前几次总结分别记录了第1-9场、第10-15场、第16-21场、第22- 25场的精彩内容（点击这里回顾）： 当宇树王兴兴、数美万物任利锋他们来到锦秋小饭桌…… 当然，我们更希望，你能来和我们一起吃吃饭，聊聊你的经历与思考。 这里先插播后续的小饭桌预告： 感兴趣的朋友可以扫码，关注锦秋基金公众账号锦秋集（ID：jqcapital），回复"锦秋小饭桌"，获得报名链接。 去改变世界! LIA 景 锦秋小饭桌开饭啦！吃饱了，咱们一起改变世界！ 锦秋小饭桌想喊你一起吃饭！ 6场饭局锦秋小饭桌一线观察：AI创业者的焦虑与突围 AI应用"吐槽大会" TIME ( 2025.09.0 ...

Core Insights - The article discusses the advancements in memory capabilities of large language models (LLMs), highlighting how companies like Google, OpenAI, and Anthropic are integrating memory features into their AI systems to enhance user interaction and continuity in conversations [1][3][10]. Memory Capabilities of LLMs - Google's Gemini has introduced memory capabilities that allow it to retain information across multiple conversations, making interactions more natural and coherent [1]. - OpenAI's ChatGPT has implemented a memory feature since February 2024, enabling users to instruct the model to remember specific details, which improves its performance over time [3][42]. - Anthropic's Claude has also added memory functionality, allowing it to recall previous discussions when prompted by the user [3][6]. Types of Memory in LLMs - Memory can be categorized into sensory memory, short-term memory, and long-term memory, with a focus on long-term memory for LLMs [16][17]. - Contextual memory is a form of short-term memory where relevant information is included in the model's context window [18]. - External memory involves storing information in an external database, allowing for retrieval during interactions, which is a common method for building long-term memory [22][23]. - Parameterized memory attempts to encode information directly into the model's parameters, providing a deeper form of memory [24][29]. Innovations in Memory Systems - New startups are emerging, focusing on memory systems for AI, such as Letta AI's MemGPT and RockAI's Yan 2.0 Preview, which aim to enhance memory capabilities [11][12]. - The concept of hybrid memory systems is gaining traction, combining different types of memory to improve AI's adaptability and performance [37][38]. Notable Memory Implementations - OpenAI's ChatGPT allows users to manage their memory entries, while Anthropic's Claude retrieves past conversations only when requested [42][44]. - Gemini supports user input for memory management, enhancing its ability to remember user preferences [45]. - The M3-Agent developed by ByteDance, Zhejiang University, and Shanghai Jiao Tong University integrates long-term memory capabilities across multiple modalities, including video and audio [10][70]. Future Trends in AI Memory - The future of AI memory is expected to evolve towards multi-modal and integrated memory systems, allowing for a more comprehensive understanding of user interactions [97][106]. - There is a growing emphasis on creating memory systems that can autonomously manage and optimize their memory, akin to human cognitive processes [101][106]. - The ultimate goal is to develop AI systems that can exhibit unique personalities and emotional connections through their memory capabilities, potentially leading to the emergence of artificial general intelligence (AGI) [109][110].