Unmanned Aerial Vehicles (UAVs) are increasingly important in dynamic environments such as logistics transportation and disaster response. However, current tasks often rely on human operators to monitor aerial videos and make operational decisions. This mode of human-machine collaboration suffers from significant limitations in efficiency and adaptability. In this paper, we present AirVista-II—an end-to-end agentic system for embodied UAVs, designed to enable general-purpose semantic understanding and reasoning in dynamic scenes. The system integrates agent-based task identification and scheduling, multimodal perception mechanisms, and differentiated keyframe extraction strategies tailored for various temporal scenarios, enabling the efficient capture of critical scene information. Experimental results demonstrate that the proposed system achieves high-quality semantic understanding across diverse UAV-based dynamic scenarios under a zero-shot setting.

As the next-generation Internet characterized by readability, writability, and ownability, Web 3.0 necessitates the fusion of blockchain and artificial intelligence (AI) technologies to realize its vision of decentralization, user autonomy, and intelligent openness. To this end, this article proposes the integration of “AI for blockchain” and “blockchain for AI” to form a bidirectional enhancement loop, for establishing genuinely intelligent blockchains and ushering in a new paradigm referred to as blockchain intelligence. On this basis, the technical architecture of intelligent blockchains is proposed, which infuses intelligence into every layer of traditional blockchain architectures while enables the parallel execution between virtual and artificial intelligent blockchain systems. This architecture facilitates blockchain systems to cultivate an ecosystem of intelligence, extending from foundation intelligence to application intelligence. Moreover, the core attributes of blockchain intelligence are examined, from the perspectives of smart contracts, data, identity, and governance. Furthermore, the main challenges and research issues faced by blockchain intelligence are outlined. This article is committed to the advancement of blockchain intelligence, laying the groundwork for Web 3.0 and the impending era of smart societies.

The rise of Artificial Intelligence for Science (AI4S) has highlighted the importance and urgency of ensuring open-ness, fairness, impartiality, diversity, and sustainability in scientific systems. Existing scientific systems, referred to as Centralized Science (CeSci), are built on centralized organizational structures and top-down institutional frameworks, which are lagging behind the development and practical requirements of AI4S. To address these limitations, AI4S needs to embrace a new scientific organizational and operational paradigm, namely Decentralized Science (DeSci). It can provide strong support to AI4S via effectively addressing issues such as information silos, biases, unfair distribution, and monopolies and promoting multidisciplinary, interdisciplinary, and trans disciplinary cooperation in science. Based on these considerations, this paper presents the framework of AI4S based on DeSci and explores its potential application scenarios and research issues. The research can provide effective guidance for the development of scientific systems.

Empowered by blockchain and Web3 technologies, decentralized autonomous organizations (DAOs) are able to redefine resources, production relations, and organizational structures in a revolutionary manner. This article aims to reanalyze DAOs from the perspectives of organization and operation, and provide a more precise definition of DAOs as Decentralized Autonomous Organizations and Operations. Based on this, the fundamental principles and requirements of DAOs are explained, while the infrastructure based on cyber–physical–social system (CPSS) and parallel intelligence, as well as the supporting technologies, such as digital twins, metaverse, and Web3, are discussed. Besides, a five-layer intelligent architecture is presented, and the closed-loop equation and new function-oriented intelligent algorithms are also proposed. Moreover, the governance mechanisms from the individual, organizational and social perspectives are discussed, and the incentive mechanisms for the human, robot, and digital human are analyzed. This article can be regarded as a stepping stone for further research and developments of DAOs.