Core Insights - Smart materials have emerged as a cutting-edge direction in the new materials field, with the potential to profoundly change human society through deep integration with artificial intelligence [1][6] Summary by Sections Definition and Characteristics of Smart Materials - Smart materials are defined as materials that can sense environmental changes, make judgments, and execute commands, distinguishing them from traditional materials [2] - Key characteristics include the ability to actively change shape, hardness, color, and function in response to external stimuli, integrating sensing, driving, and information processing [2][3] Types and Applications of Smart Materials - At least twenty types of smart materials have been identified, including: - Piezoelectric materials for energy conversion and vibration control - Shape memory alloys used in medical devices like stents - Magnetostrictive materials for ultrasound transducers - Electrorheological and magnetorheological materials for adaptive dampers in vehicles - Self-healing materials for automotive applications [3][4][5] Integration with Artificial Intelligence - The concept of "wise materials" has been introduced, where smart materials are enhanced with AI capabilities, allowing them to make autonomous decisions and adapt to their environment [6] - Examples of applications include AI-controlled prosthetics and smart lenses that adjust focus based on eye movement [6] Market Potential and Future Outlook - The global smart materials market is projected to reach up to $250 billion by 2030, driven by advancements in AI, brain science, and biotechnology [7] - In various sectors, smart materials are expected to lead to innovations such as personalized medical treatments, green energy solutions, and enhanced safety systems [7] Current Status and Challenges - While China leads in basic research and certain advanced fields, there remains a gap in the transformation of consumer products and the establishment of an industrial ecosystem compared to developed countries [8] - Emphasis is placed on the need for interdisciplinary collaboration to accelerate product development and application [8]

Core Viewpoint - The article discusses the dual exploration of embodied intelligence in China, focusing on advancements in AI large models by companies like UBTECH and Zhihui Square, and the foundational work on intelligent materials by academician Leng Jinsong to reconstruct the "body" of robots [2][3][18]. Group 1: AI Large Models and Commercial Applications - UBTECH announced its large multimodal model, Thinker, which achieved four global firsts in international robot benchmark tests [2]. - Zhihui Square plans to deploy over 1,000 embodied intelligent robots powered by its VLA model in the semiconductor display production base of Huike over the next three years [2][14]. - The VLA model allows robots to learn tasks autonomously through end-to-end data-driven approaches, enhancing their adaptability in existing factory environments [14][15]. Group 2: Intelligent Materials and Robotic "Body" - Leng Jinsong emphasizes the importance of the "execution layer" in embodied intelligence, which is often overlooked in current discussions [2][10]. - His research focuses on intelligent materials that can actively change shape and function, aiming to replace traditional motors in robotics [5][10]. - A notable application of these materials is the flexible solar sail deployed on a commercial satellite, marking the first use of such materials as the main power source in space [7][8]. Group 3: Future Applications and Innovations - Intelligent materials have potential applications in various fields, including aerospace, industrial manufacturing, and biomedical sectors [9][10]. - Examples include flexible hydrogen storage bottles for electric vehicles and biodegradable stents for cardiovascular applications [9][10]. - Leng envisions a future where intelligent materials can not only change but also possess life-like characteristics, integrating AI and self-repair capabilities [11]. Group 4: Industry Challenges and Competitive Landscape - The competition in the industry is not only about AI algorithms but also about enhancing the sensory capabilities of robots through advanced tactile sensors [15][16]. - Despite leading in foundational research on intelligent materials, China faces the risk of being outpaced in product commercialization by companies from Japan and Germany [16]. - The article highlights the need for both AI-driven companies and foundational research to effectively translate their technological advantages into market-ready products [18].