Dual-brain fusion: Bidirectional empowerment between human brain and brain-inspired systems

Artificial intelligence (AI) is fundamentally reshaping societal futures, with its transformative applications driving profound, cross-sectoral change. From surgical robots that enhance medical precision and safety to autonomous vehicles that reconfigure transportation ecosystems, AI is accelerating social progress at an unprecedented pace and scale. Yet current AI technologies face persistent foundational challenges: overreliance on static, context-insensitive rules; limited capacity for dynamic, real-world simulation; and representation models that lack depth and integrative coherence. These limitations constrain adaptability in non-stationary environments, hinder the emergence of holistic intelligence, and obscure the mechanistic essence of true intelligence, constituting a critical barrier to artificial general intelligence (AGI). Dual-Brain Fusion, the deep, bidirectional synergy between the human brain and brain-inspired systems, represents the essential pathway to overcoming this barrier. As nature's most sophisticated intelligent system, the human brain offers fundamental insights for brain-inspired research through its capacities for multimodal perception, adaptive cognition, and goal-directed decision-making. Although existing research has advanced perception optimization, cognitive enhancement, and decision-making improvement, it remains constrained by a single-layer simulation paradigm of brain functions, incomplete understanding of neural functional mechanisms, and the absence of engineered bidirectional interaction between the two systems. To address these challenges, this paper proposes leveraging the human brain's perceptual, cognitive, and decision-making functional mechanisms as a unifying bridge, breaking down interdisciplinary barriers to construct a full-chain collaborative innovation paradigm centered on Dual-Brain Fusion, which enables mutual inspiration between the human brain and brain-inspired systems. Within this framework, brain-inspired systems are optimized using principles derived from human brain mechanisms, while empirical feedback from these systems informs refined analysis of brain functional mechanisms, establishing a closed loop of bidirectional empowerment. Looking ahead, the continued advancement of Dual-Brain Fusion will catalyze an intelligence leap grounded in brain functional mechanisms. This paradigm, anchored in brain mechanisms as a source of principled inspiration, drives AI breakthroughs at the level of intelligence itself, unlocks synergistic human–machine co-adaptation, and charts a developmental path toward human–machine symbiosis and co-evolution.