“AI原生终端”的落地时刻，如何重构端侧智能？｜CES 2026

Core Insights - The CES 2026 focuses on the practical applications of AI, moving beyond previous years' discussions on AI concepts to real-world implementations [2] - The concept of AI-native terminals is gaining traction, with discussions highlighting the need for devices that are fundamentally reliant on AI for their existence [4][6] Group 1: AI Native Terminals - AI-native terminals are defined as devices that lose their significance without AI, with a strong emphasis on the importance of finding suitable application scenarios for these technologies [4][10] - The early stages of AI-native terminal development will favor scenarios with strong consumer willingness to pay, such as education, healthcare, and tourism [10] - The distinction between traditional smart hardware and AI-native terminals lies in the latter's autonomous computing capabilities, allowing them to solve problems independently [6][12] Group 2: Market Trends and Consumer Expectations - The market is witnessing a shift towards devices that integrate AI capabilities, with expectations that all electronic devices will eventually possess AI functionalities [2][8] - There is a consensus that successful AI-native products must focus on solving specific user pain points rather than attempting to cover all functionalities [4][10] - The development of AI glasses and embodied intelligence products is seen as a promising direction, with the potential to redefine user interaction and experience [6][12] Group 3: Technical Challenges and Innovations - The integration of AI into devices faces challenges related to physical limitations such as weight and battery life, particularly in wearable technology like AI glasses [6][15] - The current approach to data processing involves a "cloud-edge-end" model, where data is analyzed in stages, but there is a push towards local processing for simpler tasks to enhance user experience [15] - Future innovations in AI glasses will require a balance between hardware advancements and software improvements, focusing on user-friendly interactions [16][21] Group 4: Industry Collaboration and Ecosystem - The relationship between hardware manufacturers, chip suppliers, and algorithm developers is evolving, with a need for collaboration to meet consumer demands effectively [19][20] - The AI hardware landscape is characterized by a shift towards open platforms that provide a comprehensive AI technology foundation, including chips, software, and tools [20] - The competitive edge of Chinese companies in the AI hardware sector is attributed to their robust supply chains and growing AI research capabilities [22][24]