东北证券发布研报称，全球数据中心存储需求市场规模呈现指数级扩容特征，形成"量级跨越+增速跃 升"双重演化态势。2024年数据量突破1.1ZB，预计2028年将攀升至2.4ZB。数据作为AI训练与推理的基 础，地位显著提升，存储成为决定AI效能的关键变量，存储技术的发展直接影响数据的规模、访问速 度、成本以及AI模型的训练效率，存储不再是简单的数据仓库，而是成为了决定AI效能的关键变量， 因此存储体系进入"容量、性能、效率"多维度协同优化的新阶段。 ...

Core Viewpoint - Google is initiating a transformation in AI architecture, moving beyond the limitations of the existing attention mechanisms with the introduction of the MoR architecture, indicating a consensus on the need for architectural innovation in the AI field [2][3]. Group 1: RockAI's Innovations - RockAI has developed the Yan architecture, which is a non-Transformer framework that significantly reduces computational complexity, allowing for offline operation on low-power devices like Raspberry Pi [5][10]. - The Yan 2.0 Preview model possesses native memory capabilities, enabling it to remember interactions over time, unlike traditional models that forget previous conversations [6][12]. - The architecture allows for end-to-end memory integration, making it easier for users as it does not require manual management of external knowledge bases [19][22]. Group 2: Challenges with Transformer Models - Transformer models face issues such as data scarcity and high computational requirements, making it difficult to deploy on low-power devices without significant modifications [9][10]. - The reliance on massive datasets for pre-training is becoming increasingly challenging due to the difficulty in acquiring high-value data [9]. - Current models often lack the ability to learn and update parameters during inference, limiting their adaptability [9][10]. Group 3: Vision for AI Development - RockAI aims to create intelligent devices that can learn and evolve independently, moving away from static models that require cloud connectivity [24][25]. - The concept of collective intelligence is emphasized, where individual devices with learning capabilities can share knowledge and evolve together, contributing to the development of AGI [26][29]. - The company’s mission is to ensure that every device possesses its own intelligence, promoting offline smart capabilities [27][28]. Group 4: Market Reception and Future Directions - RockAI's approach has gained recognition at industry events, with hardware manufacturers showing interest in their technology due to its unique memory capabilities [34][35]. - The company is committed to continuing its challenging yet correct technological path, focusing on enhancing autonomous learning capabilities [36][37]. - RockAI's long-term vision reflects a commitment to fundamental technological advancements, akin to the journeys of leading AI research labs [37][38].