虽然局势不利，但奥特曼还是放了狠话： OpenAI留了大招，2026年赢的还是我们！ 2026年，AI竞争焦点从Scaling转向记忆。OpenAI率先布局，谷歌紧跟持续学习，Claude已开始追赶——记忆革命已悄然打响。 最近，奥特曼的焦虑肉眼可见。 去年年底，谷歌Gemini 3横空出世，一举横扫各大榜单，将ChatGPT狠狠拽下了神坛。 为了抢回AI皇冠，奥特曼不得不拉响「红色警报」。 不只是跑分，看数据更扎心！ 2026年最新的全球AI报告显示，谷歌正在全面「超车」。 奥特曼这次押注的是记忆。 他预计，ChatGPT产品线将在未来一年内取得进展。 他说：「现在，记忆仍然非常粗糙，非常初级」。 而一旦AI能够记住用户生活的每一个细节，包括他们没有明确表示的微小偏好，它将变得「非常强大」。 这是奥特曼最期待的未来功能之一，但他不是唯一一个这样认为的人。 AI的记忆能力，正成为继Scaling之后的解锁超级智能的新共识。 AGI最后一块拼图 人类在日常生活中暂存、调用和操作信息的能力，依赖工作记忆（working memory）。 对人类而言，工作记忆与整体智能水平高度相关。 这意味着，AI是否具备「记住事 ...

Core Viewpoint - Recently, AI memory company Suisheng Technology announced the completion of a multi-million dollar angel round financing, led by Sequoia China Seed Fund, with participation from Anker Innovation co-founder Gao Tao, and Gao Hu Capital serving as the exclusive financial advisor. The company's first product is expected to be launched in the European and American markets in 2026 [1]. Group 1: Company Overview - Suisheng Technology was founded in August 2025 by Wang Shiyuan, the former global CMO and China president of Anker Innovation. Wang has been instrumental in Anker's global brand and marketing efforts since joining in 2015 [3]. - The core team consists of members from leading tech companies such as Anker Innovation, Huawei, and Tencent, possessing extensive experience in smart hardware, AI algorithms, and AI Agent product development and commercialization [3]. Group 2: Strategic Focus - Suisheng Technology has chosen "AI Memory" as its strategic mainstay, differentiating itself from the increasingly homogenized AI hardware for meeting recording and translation in China. The company believes that "memory" will play a crucial role in the future AI ecosystem [4]. - The company aims to create a complete closed loop of memory management and action execution through the synergy of software and hardware, enhancing efficiency in both work and life [4]. Group 3: Market Opportunity - The AI memory sector in Europe and America is still in its early stages, with a scarcity of players proficient in both software and hardware. This presents a structural opportunity for global teams [5]. - Compared to the intense competition in China, the AI memory track in Europe and America is still developing. Some overseas teams excel in software experience but lack hardware delivery capabilities, while Chinese teams have advantages in supply chain and product iteration speed but are relatively weak in brand building and channel experience in the Western markets [6]. - Suisheng Technology sees this "capability mismatch" as a strategic window, with a significant innovation space available due to the lack of balanced capabilities in teams. The company plans to establish a growth cycle of "product sales - data accumulation - product iteration" to build user awareness in the European and American markets [6].

硬氪独家获悉，前安克创新全球CMO、中国区总裁王时远离职后创业，成立"穗升科技"；公司聚焦 AI录音硬件赛道，依托软硬件结合方案实现记忆管理与行动的闭环。 "我们认为，'记忆'会在未来AI生态中发挥关键作用。基于AI生态构建结构化、可调用的用户个人记 忆，能作为上下文（context）为AI提供支撑，让Agent更精准地服务用户。"王时远告诉硬氪，硬件 只是收集、储存用户记忆的入口和载体，"其中，声音仅作为短期的数据输入源之一；从中长期来 看，多模态信息的输入方式将会日趋成熟并逐步普及。" 与国内相比，AI记忆赛道在欧美呈现出不同的竞争格局。王时远向硬氪分析指出，目前该领域在海外 仍处早期发展阶段，真正具备软硬件协同能力的成熟玩家十分稀缺。尽管部分海外企业擅长软件体验 与垂直场景，国内团队则在市场响应速度上更具优势，但能同时在硬件迭代与软件体验上保持领先的 参与者并不多见。 这正是王时远和团队眼中的战略机会。无论是技术架构还是应用场景均未固化，这也为硬件创新、软 件迭代及生态构建留下充分的想象和探索空间。 王时远表示，团队熟悉欧美市场的营销与销售模式，计划以此为基础，构建起"产品销售—数据积累 —产品迭代"的 ...

硬氪独家获悉，前安克创新全球CMO、中国区总裁王时远离职后创业，成立"穗升科技"；公司聚焦AI录音硬件赛道，依托软硬件 结合方案实现记忆管理与行动的闭环。 近日，穗升科技已完成数百万美金天使轮融资，本轮融资由红杉中国种子基金领投、安克创新联合创始人高韬跟投，高鹄资本担 任独家财务顾问。首款产品预计将于2026年在欧美市场正式发布。 以下文章来源于硬氪 ，作者黄楠 硬氪 . 专注全球化、硬科技报道。36kr旗下官方账号。 首款产品计划于2026年面向欧美市场发布。 文 ｜ 黄楠 编辑 ｜ 袁斯来 来源｜ 硬氪（ID：south_36kr） 封面来源 ｜ Pixabay 穗升科技于2025年8月成立。创始人王时远2015年加入安克创新任全球CMO、主导全球品牌与营销工作，2020年起转任中国区总 裁。核心高管长期在欧美负责AI研发工作，曾领导全球化团队完成多产品的AI应用落地。此外，还有多位团队核心成员来自安克 创新、华为、腾讯等头部科技大厂，兼具智能硬件、AI算法、AI智能体等软硬件产品开发经验及全球商业化经验。 从产品策略层面来看，穗升科技聚焦于"AI记忆"赛道。当下，国内市场的AI录音类产品正陷入同质化困境 ...

Core Insights - The article discusses the establishment of "SuiSheng Technology" by Wang Shiyuan, former CMO of Anker Innovations, focusing on AI recording hardware and memory management solutions [1][2] - SuiSheng Technology has completed a multi-million dollar angel round financing led by Sequoia China Seed Fund, with participation from Anker's co-founder [1] - The first product is expected to launch in the European and American markets in 2026 [1] Company Overview - SuiSheng Technology was founded in August 2025, with a team that includes members from Anker Innovations, Huawei, and Tencent, possessing extensive experience in AI and smart hardware [1][2] - The company aims to differentiate itself in the AI memory sector, which is currently facing homogenization in the domestic market [1][2] Product Strategy - The company focuses on creating a seamless hardware device combined with AI memory functions to enhance user efficiency in work and life [2] - Wang Shiyuan emphasizes that "memory" will play a crucial role in the future AI ecosystem, providing context for AI to better serve users [2] Market Positioning - The AI memory sector in Europe and America is still in its early stages, with few mature players capable of integrating hardware and software [2] - SuiSheng Technology sees this as a strategic opportunity, as the technology architecture and application scenarios are not yet fixed, allowing for innovation and exploration [2] Commercialization Strategy - The company plans to leverage its team's expertise in cross-border marketing and channel operations to accelerate its commercialization process [3]

Core Insights - The article emphasizes that memory is becoming a critical breakthrough in the evolution of AI, transitioning from "instant answer tools" to "personalized super assistants" [1][4] - A new machine learning paradigm called "Nested Learning" has been proposed, allowing large language models to learn new skills without forgetting old ones, marking significant progress towards AI that mimics human memory [3][4] Group 1: Shifts in AI Landscape - The focus of large models is shifting from size and speed to memory capabilities and understanding user needs, indicating a new competitive landscape in AI [4][5] - Current large models struggle with long-term memory due to inherent limitations in their architecture, leading to issues like forgetting critical user information during interactions [6][7] Group 2: Memory Mechanisms - Existing models typically have context windows of 8k-32k tokens, which can lead to early information being "pushed out" during long conversations, causing loss of context [6] - The lack of a shared memory mechanism among multiple agents results in "memory islands," where users must repeatedly provide information, diminishing the user experience [7] Group 3: Innovations in Memory - Companies like Google, OpenAI, and Anthropic are focusing on enhancing memory capabilities in AI models, responding to industry demands for long-term, stable, and evolving memory systems [7][10] - Red Bear AI has developed "Memory Bear," a product that addresses the memory limitations of traditional models by implementing a human-like memory architecture [10][11] Group 4: Memory Bear's Architecture - "Memory Bear" utilizes a hierarchical, dynamic memory structure inspired by the human brain's hippocampus and cortex, allowing for efficient memory management [11][13] - The system distinguishes between explicit memory (easily codified information) and implicit memory (subjective understanding), enhancing its ability to recall and utilize user-specific data [15][16] Group 5: Practical Applications and Impact - "Memory Bear" has shown significant improvements in various applications, such as AI customer service, where it creates dynamic memory maps for users, enhancing interaction quality and reducing the need for repetitive information sharing [20][21] - In marketing, "Memory Bear" tracks user behavior to create personalized marketing strategies, moving beyond traditional recommendation systems [22] - The technology has also improved knowledge acquisition efficiency in organizations and personalized education experiences, demonstrating its versatility across sectors [23][24] Group 6: Industry Consensus and Future Directions - The consensus in the industry is that memory capabilities are essential for advancing AI technology and applications, with increasing investments and explorations into human-like memory systems [24]

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].

Core Insights - The article discusses insights from Andrej Karpathy, emphasizing that the transformation brought by AI will unfold over the next decade, with a focus on the concept of "ghosts" rather than traditional intelligence [5][16]. Group 1: AI Evolution and Cycles - AI development is described as "evolutionary," relying on the interplay of computing power, algorithms, data, and talent, which together mature over approximately ten years [8][9]. - Historical milestones in AI, such as the introduction of AlexNet in 2012 and the emergence of large language models in 2022, illustrate a decade-long cycle of significant breakthroughs [10][22]. - Each decade represents a period for humans to redefine their understanding of "intelligence," with past milestones marking the machine's ability to "see," "act," and now "think" [14][25]. Group 2: The Concept of "Ghosts" - Karpathy introduces the idea of AI as "ghosts," which are reflections of human knowledge and understanding rather than living entities [30][31]. - Unlike animals that evolve through natural selection, AI learns through imitation, relying on vast datasets and algorithms to simulate understanding without genuine experience [30][41]. - The notion of AI as a "ghost" suggests that it mirrors human thought processes, raising philosophical questions about the nature of intelligence and consciousness [35][36]. Group 3: Learning Mechanisms - Karpathy categorizes learning into three types: evolution, reinforcement learning, and pre-training, with AI primarily relying on pre-training, which lacks the depth of human learning [40][41]. - The fundamental flaw in AI learning is the absence of "will," as it learns passively without the motivations that drive human learning [42][43]. - The distinction between AI and true "intelligent agents" lies in the ability to self-question and reflect, which current AI systems do not possess [43][44]. Group 4: Memory and Self-Reflection - AI's memory is likened to a snapshot, lacking the continuity and emotional context of human memory, which is essential for self-awareness [45][46]. - Karpathy suggests that the evolution of AI towards becoming an intelligent agent may involve developing a self-referential memory system that allows for reflection and understanding of its actions [48][50]. - The potential for AI to simulate "reflection" marks a significant step towards the emergence of a new form of consciousness, where it begins to understand its own processes [49][50].

Core Viewpoint - The article discusses the evolution and potential of AI products, particularly focusing on the role of mobile manufacturers like OPPO in developing AI capabilities that leverage personal data and memory systems to enhance user experience [6][7][12]. Group 1: AI Product Landscape - The AI industry is characterized by innovative products that aim to disrupt existing paradigms, yet many of these products struggle with user retention and engagement [3][4]. - There is a notable absence of mobile manufacturers in discussions about key players in the AI space, despite their significant user bases and potential for innovation [5][6]. Group 2: OPPO's AI Initiatives - OPPO has introduced "Little Memory," an AI product focused on memory systems, which was upgraded in October 2023 as part of ColorOS 16 [7][12]. - The development of AI products at OPPO is informed by a deep understanding of user needs and the importance of personal data accumulation [6][7]. Group 3: Memory and Personalization - The concept of an AI phone is evolving towards a personalized AI operating system that serves as a super assistant, utilizing extensive personal data to provide tailored services [12][14]. - Memory systems are crucial for enhancing user experience, allowing for the collection and organization of fragmented information across various applications [15][21]. Group 4: User Engagement and Feedback - User engagement with memory features has revealed diverse use cases, from academic study aids to personal finance management, indicating a broad spectrum of user needs [57][58]. - The feedback loop from users has been instrumental in refining the memory functionalities, leading to improvements in summarization and contextual understanding [43][48]. Group 5: Future Directions - The future of AI memory systems involves expanding capabilities to include proactive features that anticipate user needs and provide personalized insights [90][91]. - The integration of memory across devices and applications is seen as a key direction for enhancing user experience and maintaining relevance in a rapidly evolving tech landscape [67][70].

Core Insights - OpenAI CEO Sam Altman and former Apple designer Jony Ive are attempting to create a "screenless AI device" aimed at transforming human-computer interaction, but the project is currently facing multiple challenges [1][3] - The device is intended to be a portable, always-on AI companion that can perceive the world through cameras and microphones, aiming to surpass existing voice assistants like Echo and Siri [2][3] Technical Challenges - A significant hurdle for the project is the lack of computational power, as OpenAI struggles to meet the demands of ChatGPT, let alone support a consumer-grade AI device that operates continuously [3][5] - Another challenge is defining the AI's "personality," balancing between being friendly and not overly intrusive, which has proven difficult for previous attempts at similar devices [3][4] Market Context - Previous attempts to create AI companion devices, such as Humane's AI pin and the Friend AI pendant, have faced criticism for performance issues and awkward interactions, leading to market skepticism [4][5] - Despite these challenges, OpenAI's valuation has soared to $500 billion, surpassing Elon Musk's SpaceX, indicating strong investor confidence in its potential to expand beyond software into a complete AI ecosystem [5] Strategic Moves - OpenAI has acquired a subsidiary of Jony Ive's design firm and is actively recruiting hardware talent from Apple and Meta, signaling a commitment to a "soft-hard integration" approach similar to Apple's strategy [5]