Core Insights - The article discusses the significant shift of artificial intelligence (AI) from cloud-based solutions to edge computing, driven by the explosion of computing power and increasing privacy concerns. This transition is termed the "downward revolution" in AI, which is expected to create new opportunities in the industry [1][2]. Industry Developments - The Ministry of Commerce and eight other departments in China have issued guidelines to accelerate innovation in AI terminal products, emphasizing the need for collaboration between supply and demand [1][2]. - Major tech companies, including Meta, OpenAI, NVIDIA, Lenovo, and JD.com, are making significant advancements in edge AI, indicating a competitive landscape that is heating up [1][3]. - According to Tianfeng Securities, the combination of policy support and industry leadership is expected to lead to a major cycle of innovation in edge AI products, with 2026 projected to be a pivotal year [1][3]. Market Potential - The demand for edge AI is driven by user needs for real-time processing, data privacy, and personalized experiences. Edge AI reduces reliance on cloud computing resources, thereby enhancing user experience and privacy protection [2][6]. - The Chinese edge AI market is projected to grow from less than 200 billion yuan in 2023 to over 1.9 trillion yuan by 2028, with a compound annual growth rate (CAGR) of 58% [6][7]. Competitive Landscape - Companies are intensifying their efforts in edge AI, with OpenAI planning to launch several AI hardware products in the coming year, including smart speakers and smart glasses [3][6]. - Lenovo is also making strides in edge AI, with its upcoming Moto X70 Air smartphone expected to feature advanced AI capabilities, positioning it as a strong competitor to Apple's products [3][4]. Technological Innovations - The trend towards smaller AI models for edge devices is gaining traction, with companies focusing on practical performance and power efficiency rather than just increasing model parameters [7][8]. - Lenovo has introduced technologies such as model compression and inference acceleration engines to enhance the performance of AI PCs, achieving capabilities comparable to cloud-based models [9][11]. Future Outlook - The integration of edge and cloud AI is seen as crucial for enhancing overall AI performance, with companies like Lenovo developing platforms that facilitate seamless collaboration between devices [11][12]. - The maturation of model miniaturization technology and continuous upgrades in hardware components are expected to lead to a significant explosion in AI terminal products, benefiting domestic manufacturers [14].