A New Era of Chinese Innovation Driven by AI Hardware and Deep Economy

A New Technological Revolution Reshaping the

World The world is currently facing a wave of technological revolution and industrial transformation. In this turbulent environment, taking control of technological leadership is fundamental to a nation’s development and security. China has made clear its commitment to self-driven innovation as a strategic choice to achieve Chinese-style modernization and adapt to complex external conditions. This is not merely a policy slogan but a key paradigm for scientific and technological innovation. Specifically, it involves evaluating historical leaps, addressing existing gaps, and persistently pursuing breakthroughs with strategic determination. A critical challenge is promoting “zero-to-one innovation,” strengthening basic research, and ensuring that scientific and technological achievements cross the “valley of death” to reach the market. Furthermore, through “AI+” initiatives, intelligent technologies are expected to support scientific research and industrial upgrades, driving transformation across various industries.

The Future of AI Hardware Lies in

“Externalization of Emotions” A noteworthy paradigm has emerged in the evolution of AI hardware: the concept of “externalization of emotions.” This idea is rooted in the age-old psychological mechanism where humans delegate their emotions and psychological desires to external devices or systems. While seemingly counterintuitive, it aligns with human nature. The most successful AI products may not merely serve as highly efficient assistants but as “partners” capable of empathizing with users and understanding their emotions. This perspective has the potential to fundamentally change AI hardware design philosophies. Instead of focusing solely on efficiency and processing power, prioritizing emotional connections with humans could be the key to shaping next-generation AI products.

Transitioning Economic Paradigms to “Deep

Economy” The advancement of AI is transforming economic paradigms from standardized scalability to “deep economy.” Deep economy refers to an economic model that delves deeply into the value of time within a given space, shifting the focus of value to “exclusive value” with heightened situational relevance and the fulfillment of new desires. In this transition, businesses must shift from traditional strategies focused on scale efficiency to strategies that aim to explore deep consumer demand and enhance value density. Realizing deep customization based on “aggregation capability” and creating innovative business models centered on temporal and spatial value becomes crucial. Ultimately, the transition to AI-driven deep economy will form the backbone of corporate growth strategies.

Chinese Corporations Transforming from

“Followers” to “Explorers” Chinese corporations are undergoing a paradigm shift in their research and development models, transitioning from “followers” to “explorers.” Rather than replicating monopolistic research systems like Bell Labs, they are forming new global R&D structures based on AI, driven by national strategies, and supported by open cooperation models. This shift signifies not only technological progress but also innovation in the methods of creating breakthroughs. Companies are strengthening internal R&D while fostering collaboration with external entities and ecosystems to explore broader and deeper technological frontiers.

Human-AI “Improvisational Collaboration”

Will Shape Organizational Futures As AI becomes deeply integrated into organizational operations, the core challenge evolves beyond improving AI’s computational capabilities. The question is how humans and AI can collaborate efficiently in highly uncertain environments and generate instant innovation. The capability foundation of future organizations will not lie in one-way models like “humans adapting to machines” or “technology-led decision-making.” Instead, “human-machine improvisation,” where humans and AI dynamically interact to solve tasks in real-time, is proposed as a new paradigm that will determine organizational efficiency and innovation. This paradigm addresses the fundamental question of how to merge human creativity with AI’s processing power.

The Challenge of Governing Autonomous Agents

The rise of autonomous AI agents brings new challenges. When agents move beyond mere execution of commands to making their own judgments and actions, bridging the cognitive gap between humans and machines becomes critical. Human intentions are complex, ambiguous, multifaceted, and nuanced, making alignment with AI not just a technical challenge but a broader concern. When the powerful capabilities of “adaptability” collide with the safety boundaries of “controllability,” are we truly prepared to accept such digital assistants? While agents enhance efficiency and drive innovation, risks such as “quiet drift” in goal functions and potential dangers that contradict human intentions persist. This represents a profound challenge posed by technological advancement to human control logic.

Practical Examples Demonstrating Diverse

Paths to Innovation Beyond theoretical discussions, practical examples showcase diverse paths to innovation in China. Zhang Xue Motorcycle’s Milestone: In the 2026 World Superbike Championship (WSBK), a Chinese-manufactured motorcycle achieved its first victory. This triumph was not merely a technical breakthrough but resulted from the efficient integration of three distinct types of knowledge: scientific knowledge, craftsmanship knowledge, and entrepreneurial knowledge. It vividly demonstrates the pathway to advancing manufacturing industries to higher levels. Yiwu’s Sustainable Vitality Model: Yiwu, a county-level city in central Zhejiang, sustains remarkable vitality not by relying solely on resource endowment or favorable policies but through a dynamic business environment fostering mutual efforts between policymakers and entrepreneurs. This model embodies co-construction through marketization, co-governance through rule of law, and coexistence through internationalization, providing fertile ground for grassroots entrepreneurial spirit to thrive and grow. LandSpace’s Strategic Decisions: In the commercial spaceflight sector, LandSpace has anchored its strategy on liquid oxygen methane technology and established core capabilities through heavy capital investment. This has transformed the company from a follower to a technological leader. Hejun Education Town’s Indigenous Development: By adopting a unique approach of “academy culture + business education,” Hejun Education Town fosters diverse industries and embarks on a path of rural revitalization through “cultural blood infusion—industrial revenue growth—local reinvestment.”

Outlook for the Future:

The Fusion of Deep Economy and AI Overall, China’s current scientific and technological innovation is closely tied to the transformation of economic paradigms rather than isolated technological breakthroughs. The “externalization of emotions” in AI hardware evolution explores new relationships between technology and humanity. Simultaneously, the concept of “deep economy” vividly illustrates the future of an AI-driven economy. Companies must shift their strategies from scaling logic to value density logic, from standardization to deep customization, and build “aggregation capabilities.” In organizations, cultivating human-AI “improvisational collaboration” capabilities will be an essential factor for competitiveness. The governance challenges posed by autonomous agents foreshadow the ethical and societal issues arising from technological progress, requiring deeper discussions in the future. Practical cases like Yiwu and Zhang Xue Motorcycle highlight the diverse manifestations of innovation and provide valuable guidance for the transformation and advancement of China’s industries. Amid the waves of new technological revolutions, China’s efforts to promote self-driven innovation and transition to deep economy are not only shaping its domestic economic development but are also becoming a crucial focus in shaping the global future of technology and economics.