Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces

Abstract

The integration of artificial intelligence (AI) and brain–computer interfaces (BCIs) represents a significant advancement in neurotechnology, with broad potential applications in healthcare, communication, and human augmentation. This study examines the synergy between DeepSeek, a leader in efficient, open-source AI models, and next-generation BCI technologies. We analyze DeepSeek's contributions to model training efficiency, adaptive reasoning, and open-source accessibility, and propose a framework for BCI development that incorporates these innovations. Additionally, we explore how AI-driven neural signal processing, hardware optimization, and ethical AI–BCI systems can address the critical limitations of current BCI technologies, including signal fidelity, scalability, and real-world applicability. Finally, we offer recommendations for interdisciplinary collaboration, regulatory improvements, and equitable technology dissemination to foster the sustainable development of AI–BCI technology.