手机芯片，需要这些创新

Core Insights - The article discusses the evolution of smartphones into intelligent, context-aware devices through the integration of agentic AI, transforming them from simple communication tools into proactive digital companions [1][3]. Hardware Challenges - The main challenge in implementing agentic AI on smartphones lies in hardware limitations, including battery life, processing power, and memory constraints [3]. - To meet the demands of agentic AI, significant upgrades in smartphone hardware components such as processors, memory, storage, batteries, sensors, and thermal management are necessary [3]. Memory System Requirements - There is a growing demand for advanced memory subsystems to efficiently deliver data for AI applications on devices [6]. - The current standard LPDDR5X offers speeds up to approximately 10.7 Gbps, while the upcoming LPDDR6 standard promises even faster bandwidth (14.4 Gbps+) and improved power efficiency [6]. Innovative Technologies - Processing-in-Memory (PIM) challenges the traditional von Neumann architecture by integrating computing capabilities directly into memory, significantly reducing latency and power consumption [8]. - Advanced packaging techniques and wide I/O interfaces can enhance bandwidth and assist in thermal management, which is crucial for AI-intensive workloads [12]. Collaboration and Standardization - The success of agentic AI in mobile devices requires deep collaboration among SoC designers, memory and storage suppliers, OEMs, OS developers, and AI researchers [15]. - Organizations like JEDEC are accelerating the standardization of technologies such as LPDDR6 to ensure interoperability and innovation in the industry [15]. Industry Call to Action - The article emphasizes that the race is not just for faster processors but a collective industry effort to unlock the transformative potential of agentic AI, positioning smartphones as intelligent partners in daily life [16].