火山引擎携手厂商共同推动手机 AI 应用迈向智能化、全能化新高度
Cai Fu Zai Xian·2025-06-18 02:56

Core Insights - The integration of large models into smart terminals is driving a comprehensive upgrade of AI capabilities in mobile phones, enhancing features like smart photography, voice interaction, and image processing [1][2] - The future of mobile AI will see deeper integration with voice assistants and native OS functions, creating a more personalized and efficient user experience [2][4] Group 1: AI Integration and User Experience - AI technology is rapidly deepening its application in terminal scenarios, expanding the range of applications and enhancing user experience [2] - Mobile AI voice assistants are not only equipped with mainstream AI capabilities but also integrate with the phone's OS and various applications to meet complex user demands [2] - Examples include vivo's AI assistant, which has improved real-time response and reliability through integration with large models, and Nubia's advanced photo editing features [2] Group 2: Data Privacy and User Habits - Native mobile applications have inherent advantages in data privacy and accessibility, making them ideal for implementing AI functionalities and fostering user habits [3] - The AICC solution from Volcano Engine provides a secure environment for data processing, ensuring user privacy during AI operations [3] - The accumulation of user data on mobile devices supports personalized recommendations and intelligent decision-making, enhancing user loyalty [3] Group 3: Future of AI in Mobile Phones - The growing strength of AI features in mobile phones is making AI experiences a standard expectation among users [4] - Predictions indicate that as large model technology evolves, mobile AI experiences will transition from single-device to multi-device, enabling efficient collaboration across various scenarios [4] - Mobile phones are expected to become personalized intelligent assistants, capable of executing end-to-end tasks with simple commands, thereby improving quality of life and work efficiency [4]