[简介] 人工智能(AI)技术在制造业应用持续拓展和深化，通过构建一体化研发模式、自主化制造模式以及高韧性供应网络，驱动制造模式创新变革，成为推动制造业迈向智能化、高端化发展的核心力量。面向新发展阶段，需以场景化探索带动价值闭环验证，夯实高质量工业数据基础，推动AI与制造全流程深度融合，完善标准、生态与治理等发展保障要素，驱动工业AI迈向系统性的规模化应用，加速制造业智能化的全面跃迁。

[简介]在6G标准化商用初期（Day 1），无蜂窝技术受到了广泛关注。系统梳理了面向6G的无蜂窝通信所涉及的关键支撑技术，包括分布式收发机架构、信道信息获取与测量机制、频谱资源融合与灵活双工设计，以及分布式资源管理策略等。在此基础上，提出了一种基于数字孪生增强的无蜂窝传输优化方法，进一步提升了系统性能。同时，展示了面向高频段的无蜂窝大规模多天线（MIMO）试验验证结果，验证了相干联合传输在实际系统中的可行性。最后，探讨了无蜂窝大规模MIMO与通感一体化融合的潜在研究方向，为未来系统设计提供了新思路。

[Introduction]To achieve the potential performance gain of massive multiple-input multiple-output (MIMO) systems, base stations (BS) require downlink channel state information (CSI) fed back by users to execute beamforming design, especially in the frequency division duplex (FDD) systems. However, due to the enormous number of antennas in massive MIMO systems, the feedback overhead of downlink CSI acquisition is extremely large. To address this issue, deep learning (DL) techniques have been introduced to develop high-accuracy feedback strategies under limited backhaul constraints. In this paper, we provide an overview of DL-based CSI compression and feedback approaches in massive MIMO systems. Specifically, we introduce the conventional CSI compression and feedback schemes and the existing problems. Besides, we elaborate on various DL techniques employed in CSI compression from the perspective of network archittecture and analyze the advantages of different techniques. We also enumerate the applications of DL-based methods for solving practical challenges in CSI compression and feedback. In addition, we brief the remaining issues in deep CSI compression and indicate potential directions in future wireless networks.

[Introduction] In this paper, we provide a comprehensive examination of the evolution of graphics Application Programming Interface (APIs). We begin by exploring traditional graphics APIs, elucidating their distinct features and inherent challenges. This sets the stage for a detailed exploration of modern graphics APIs, with a focus on four critical design principles. These principles are further analyzed through specific case studies and categorical examinations. The paper then introduces MoerEngine, a bespoke rendering engine, as a practical case to demonstrate the real-world application of these modern principles in software engineering. In conclusion, the study offers insights into the potential future trajectory of graphics APIs, spotlighting emerging design patterns and technological innovations. It also ventures to predict the development trends and capabilities of the next generation of graphics APIs..