Group 1 - The core concept of the article revolves around the emergence of RockAI, a Shanghai-based AI startup that has developed a unique offline intelligent model architecture, distinguishing itself from traditional models like those from OpenAI and Meta [6][11][25] - The WAIC 2025 event highlighted a shift in focus from merely showcasing AI models to demonstrating practical use cases, indicating a growing demand for real-world applications of AI technology [4][30] - RockAI's Yan architecture allows for the deployment of large AI models on low-power devices, enabling real-time AI computations without the need for internet connectivity, which is particularly crucial in regions with unstable network environments [11][12][14] Group 2 - RockAI's products have gained significant traction in international markets, with strong demand for offline capabilities, especially among overseas enterprises with strict data security protocols [16][18][21] - The company aims to achieve General Artificial Intelligence (AGI) by integrating memory capabilities into its models, allowing devices to learn and adapt based on user interactions, thus enhancing personalization and decision-making support [26][27][28] - The current landscape of AI models is characterized by a decline in the "hundred model war," with many startups facing challenges, while RockAI continues to grow by addressing unmet needs in the market [30][32]

Core Viewpoint - The article discusses the advancements made by RockAI in developing a new AI model architecture that operates offline and possesses memory capabilities, marking a significant shift from traditional Transformer-based models [6][10][12]. Group 1: RockAI's Innovations - RockAI has introduced the Yan 2.0 Preview model, which features a "native memory" capability allowing it to learn and evolve continuously through user interactions [11][12]. - The model operates entirely offline, demonstrating effective performance in tasks such as learning new actions and playing games without external control [6][8][11]. - The architecture is designed specifically for edge devices, enabling efficient operation without relying on cloud resources, which is crucial for devices with limited computational power [30][48]. Group 2: Memory Mechanism - Yan 2.0 Preview incorporates a memory module that allows for dynamic updating and retrieval of information, enabling the model to forget outdated knowledge while integrating new insights [20][23]. - The model's memory retrieval mechanism selects the most relevant memories to generate outputs, enhancing its reasoning capabilities [23][24]. - This approach contrasts with traditional models that are static and unable to learn post-deployment, positioning Yan 2.0 as a more adaptive and intelligent system [14][17]. Group 3: Market Position and Future Directions - RockAI is positioned as a leader in the non-Transformer architecture space, having successfully deployed its models on various edge devices without the need for model compression or quantization [58][60]. - The company aims to create a collective intelligence framework where multiple models can collaborate and evolve, moving towards a more decentralized AI ecosystem [65][66]. - The shift away from Transformer models is seen as a response to the limitations of current architectures, with RockAI advocating for simpler algorithms that require less computational power and data [28][37].