Core Viewpoint - The article discusses five major trends in AI innovation applications as summarized by Intel's Vice President, Li Ying, during the 2025 Intel AI Innovation Competition awards ceremony held in Shenzhen [1][2]. Group 1: Trends in AI Innovation Applications - **Cloud-Edge-End Collaboration**: The collaboration among cloud, edge, and terminal devices is becoming more refined, with cloud handling large model training and global decision-making, edge focusing on localized real-time computing, and terminal devices processing privacy data locally through lightweight models [3]. - **Increased Importance of Data Security and Privacy**: Data security and privacy protection have become core requirements in AI development, with local inference rising, allowing sensitive data to remain on-site rather than being uploaded to the cloud [3]. - **Complementary Ecosystem of Traditional AI and Large Models**: Traditional AI's specialization and large models' generalization capabilities are merging, with large models leading in tasks like natural language understanding while traditional AI focuses on specific vertical applications [3]. Group 2: User Experience and Development Trends - **Humanized and Personalized Experience**: AI applications are shifting from merely functional to emotionally resonant and personalized services, utilizing emotional computing and multimodal interactions to cater to individual user needs [4]. - **Lowering Development Barriers**: The rise of low-code/no-code platforms and pre-trained models is facilitating a new era of "全民AI创新" (全民 AI Innovation), allowing developers to implement solutions with minimal data adjustments, significantly reducing development cycles [4].