Engineering最新文献_第6页

Material Removal Mechanisms in Ultra-High-Speed Machining 超高速加工中的材料去除机理

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2024.12.033

Hao Liu, Jianqiu Zhang, Qinghong Jiang, Bi Zhang

Machining high-performance engineering materials, faces challenges including low machining efficiency, poor workpiece surface integrity, and rapid tool wear, which restrict high quality and efficient machining. Ultra-high-speed machining (UHSM) has been expected to address these issues. However, the material removal mechanisms involved in UHSM remain unclear and need further exploration. This paper reviews the criteria for evaluating the ductile and brittle behaviors of high-performance materials subjected to machining, as well as the developmental history of the material’s ductile–brittle transition induced by machining, proposing the concept of relativization of ductile–brittle property. Additionally, it further summarizes three typical material removal mechanisms: ductile-mode removal based on shear stress, brittle-mode removal based on tensile stress, and extrusion removal based on compressive stress, clarifying the universality of the brittle-mode removal. On this basis, this paper focuses on the discussion of the material removal mechanisms in UHSM, including high strain-rate-induced material embrittlement, UHSM-induced skin effect of damage, and the thermal effect in UHSM. Furthermore, it provides a detailed description of the typical characteristics of chip morphology in the ductile–brittle transition region (DBTR) under the high strain rate condition and, for the first time, elucidates the material removal mechanisms in the DBTR from a microstructural dislocation perspective, enriching the basic theory of UHSM. In the discussion section, it standardizes the definition for the UHSM, and explores the dislocation movement at high strain rates and the crack propagation in the UHSM. Finally, based on the current status of the UHSM technology, it summarizes the relevant research hotspots. For the first time, this paper brings up the brittle-mode removal mechanism under ultra-high-speed conditions, which is helpful to promote the UHSM for industrial applications.

高性能工程材料的加工面临加工效率低、工件表面完整性差、刀具磨损快等挑战，制约了高性能工程材料的高质量、高效率加工。超高速加工（UHSM）有望解决这些问题。然而，超高压材料的去除机制尚不清楚，需要进一步探索。本文综述了高性能材料的加工韧脆性评价标准，以及加工诱发材料韧脆性转变的发展历史，提出了韧脆性相对化的概念。进一步总结了基于剪切应力的韧性模态去除、基于拉应力的脆性模态去除和基于压应力的挤压模态去除三种典型的材料去除机制，阐明了脆性模态去除的普遍性。在此基础上，重点讨论了超高压材料的去除机制，包括高应变率诱导的材料脆化、超高压损伤的集肤效应和超高压材料的热效应。详细描述了高应变率条件下韧脆过渡区（DBTR）中切屑形貌的典型特征，并首次从微观组织位错的角度阐述了材料在DBTR中的去除机理，丰富了超高温超导的基础理论。在讨论部分，规范了超高压合金的定义，探讨了超高压合金在高应变速率下的位错运动和裂纹扩展。最后，基于超高频超导技术的现状，总结了相关的研究热点。本文首次提出了超高速条件下脆性模态去除机理，有助于推动超高速超导材料的工业化应用。

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引用次数: 0

Self-Adaptive Core–Shell Dry Adhesive with a “Live Core” for High-Strength Adhesion Under Non-Parallel Contact 具有“活芯”的自适应核-壳干胶粘剂，用于非平行接触下的高强度粘附

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2024.12.035

Duorui Wang , Hongmiao Tian , Jinyu Zhang , Haoran Liu , Xiangming Li , Chunhui Wang , Xiaoliang Chen , Jinyou Shao

Gecko-inspired van der Waals force-based adhesion technology demonstrates significant potential for robotic operations. While superior adhesion is achieved under parallel contact during testing, engineering operations often involve non-parallel contact, weakening adhesion, and compromising task stability and efficiency. Stable attachment under such non-parallel contacts remains challenging. Inspired by the soft muscle and rigid bone in the gecko’s sole, this study proposes a self-adaptive core–shell dry adhesive by embedding a thin, rigid piece into a soft, thick elastomer comprising a top adhesion tip with a mushroom-like geometry for interfacial adhesion based on the van der Waals force and a bottom core–shell configuration for interface stress regulation. Unlike traditional core–shell structures with a fixed “dead core,” the proposed “live core” rotates within the soft shell, mimicking skeletal joints. This enables stress equalization at the interface and facilitates adaptive contact to macroscopic interfacial angle errors. This innovative core–shell configuration demonstrates an adhesion strength 100 times higher than conventional homogeneous structures under non-parallel contact and offers anti-overturning ability by mitigating torsional effects. The proposed strategy can advance the development of gecko-inspired adhesion-based devices and systems.

受壁虎启发的范德华力黏附技术显示了机器人操作的巨大潜力。虽然在测试过程中，在平行接触下可以获得较好的粘附性，但在工程操作中，非平行接触往往会导致粘附性减弱，从而影响任务的稳定性和效率。在这种非平行接触下稳定的附着仍然具有挑战性。受壁虎鞋底的软肌肉和刚性骨骼的启发，本研究提出了一种自适应的核壳干胶，通过将薄而刚性的块嵌入软而厚的弹性体中，该弹性体包括具有基于范德华力的界面粘附的蘑菇状几何形状的顶部粘附尖端和用于界面应力调节的底部核壳结构。与具有固定“死核”的传统核壳结构不同，拟议的“活核”在软壳内旋转，模仿骨骼关节。这使得界面应力均衡，有利于宏观界面角误差的自适应接触。这种创新的核-壳结构在非平行接触下的粘附强度比传统的均匀结构高100倍，并通过减轻扭转效应提供抗倾覆能力。所提出的策略可以促进壁虎启发的粘合剂为基础的设备和系统的发展。

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引用次数: 0

A Soft Tactile Unit with Three-Dimensional Force and Temperature Mathematical Decoupling Ability for Robots 具有三维力与温度数学解耦能力的机器人软触觉单元

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.02.008

Xiong Yang , Hao Ren , Dong Guo , Zhengrong Ling , Tieshan Zhang , Gen Li , Yifeng Tang , Haoxiang Zhao , Jiale Wang , Hongyuan Chang , TszKi Gao , Jia Dong , Ningxin Wu , Yajing Shen

Human skin exhibits a remarkable capability to perceive contact forces and environmental temperatures, providing complex information that is essential for its subtle control. Despite recent advancements in soft tactile sensors, accurately decoupling signals—specifically separating forces from directional orientation and temperature—remains a challenge thus resulting in failure to meet the advanced application requirements of robots. This study proposes, F³T, a multilayer soft sensor unit designed to achieve isolated measurements and mathematical decoupling of normal pressure, omnidirectional tangential forces, and temperature. We developed a circular coaxial magnetic film featuring a floating mount multilayer capacitor that facilitated the physical decoupling of normal and tangential forces in all directions. Additionally, we incorporated an ion gel-based temperature-sensing film into the tactile sensor. The proposed sensor was resilient to external pressures and deformations, and could measure temperature and significantly eliminate capacitor errors induced by environmental temperature changes. In conclusion, our novel design allowed for the decoupled measurement of multiple signals, laying the foundation for advancements in high-level robotic motion control, autonomous decision-making, and task planning.

人体皮肤表现出感知接触力和环境温度的非凡能力，为其微妙的控制提供了必要的复杂信息。尽管软触觉传感器最近取得了进展，但准确解耦信号-特别是将力与方向方向和温度分离-仍然是一个挑战，因此无法满足机器人的高级应用要求。本研究提出了F3T，一种多层软传感器单元，旨在实现法向压力、全方位切向力和温度的隔离测量和数学解耦。我们开发了一种具有浮动安装多层电容器的圆形同轴磁膜，促进了所有方向上法向力和切向力的物理解耦。此外，我们在触觉传感器中加入了一种基于离子凝胶的温度传感膜。该传感器对外部压力和变形具有弹性，可以测量温度并显著消除环境温度变化引起的电容误差。总之，我们的新设计允许对多个信号进行解耦测量，为高级机器人运动控制，自主决策和任务规划的进步奠定了基础。

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引用次数: 0

Simultaneous Denitrification and Decarbonization of Wastewater over In Situ Generation of ·ClO Radicals Through a Fast, High-Performance Electro-Filtration Process 通过快速、高性能的电过滤过程在原位产生·ClO自由基的废水中同时反硝化和脱碳

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.07.016

Bin Zhao , Jialin Yang , Ruiping Liu , Jiuhui Qu , Meng Sun

The contamination of wastewater with organic pollutants and nitrogen compounds poses significant environmental challenges. The primary objective of wastewater treatment is the simultaneous denitrification and decarbonization of ammonia nitrogen and organics into harmless by-products. This study presents a novel method for the directional generation of chlorine radical species like ·ClO and ·Cl using electro-reactive membranes (EMs) known as RuO₂@PbO₂-M, which were fabricated using an electro-deposition coupled template approach. This method facilitates the rapid and efficient conversion of ammonia to nitrogen and concurrently reduces the chemical oxygen demand in the effluent. Our system achieved ultra-efficient simultaneous denitrification and decarbonization with minimal energy consumption in single-filtration mode, thereby eliminating the need for chemical precursors. We elucidate the formation pathway of ·ClO and ·Cl during the electrochemical oxidation process involving RuO₂@PbO₂-M, where ·Cl generated from RuO₂ reacts with ·OH from PbO₂ under hypochlorous acid conditions, thereby enhancing nitrogen and carbon removal. These findings highlight a novel electro-filtration and an innovative reactive membrane design for ·ClO synthesis, which provides a new research framework for the concurrent removal of nitrogen and carbon, and offers a promising solution to enhance wastewater treatment efficiency.

有机污染物和氮化合物对废水的污染构成了重大的环境挑战。废水处理的主要目的是将氨氮同时脱氮脱碳为无害副产物。本研究提出了一种利用电反应膜（EMs）定向生成氯自由基（如·ClO和·Cl）的新方法，该电反应膜采用电沉积耦合模板方法RuO2@PbO2-M制备。该方法有利于氨快速有效地转化为氮，同时降低了出水中的化学需氧量。我们的系统在单过滤模式下以最小的能耗实现了超高效的同时脱氮和脱碳，从而消除了对化学前体的需求。我们阐明了在涉及RuO2@PbO2-M的电化学氧化过程中，由RuO2生成的·Cl与PbO2中的·OH在次氯酸条件下发生反应，从而促进氮和碳的去除。这些发现强调了一种利用单通道电过滤和创新的反应膜设计进行·ClO合成的新型过滤模型，为同时去除氮和碳提供了新的研究框架，并为提高废水处理效率提供了一个有希望的解决方案。

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引用次数: 0

Construction Robotics in Extreme Environments: From Earth to Space 极端环境下的建筑机器人：从地球到太空

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2024.11.037

Ke You , Cheng Zhou , Lieyun Ding , Yuxiang Wang

Extreme environments are unstructured and change rapidly, making human exploration in unfamiliar areas difficult. Construction robotics can help reduce risks to human safety and property in these environments by integrating digital technology and artificial intelligence. This technology has the potential to significantly improve the quality and efficiency of construction, making it a key area for future research. Extreme environments include hazardous work sites, polluted areas, and harsh natural conditions. Our review of construction robotics in these settings highlights several knowledge gaps. We focused on four main areas: mechanism design, perception, planning, and control. Our analysis reveals challenges in practical applications, such as creating adaptable mechanisms, accurately perceiving changing environments, planning for unstructured sites, and optimizing control models. Future research should explore: biomimetic designs inspired by nature, multimodal data fusion for perception, adaptive planning strategies, and hybrid control models that combine data-driven and mechanism-based approaches.

极端环境是非结构化的，变化迅速，使人类在不熟悉的地区进行探索变得困难。建筑机器人可以通过集成数字技术和人工智能，帮助减少这些环境中对人类安全和财产的风险。这项技术具有显著提高建筑质量和效率的潜力，使其成为未来研究的关键领域。极端环境包括危险工作场所、污染区域和恶劣的自然条件。我们对建筑机器人在这些环境中的回顾突出了几个知识空白。我们着重于四个主要领域：机制设计、感知、规划和控制。我们的分析揭示了实际应用中的挑战，例如创建适应性机制，准确感知变化的环境，规划非结构化站点以及优化控制模型。未来的研究应该探索：受自然启发的仿生设计，感知的多模态数据融合，适应性规划策略，以及结合数据驱动和基于机制的方法的混合控制模型。

引用次数: 0

The Convergence of Artificial Intelligence and Microfluidics in Drug Research and Development 人工智能与微流体技术在药物研发中的融合

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.07.025

Du Qiao , Hongxia Li , Xue Zhang , Xuhui Chen , Jiang Zhang , Jianan Zou , Danyang Zhao , Weiping Zhu , Xuhong Qian , Honglin Li

Drug research and development (R&D) plays a crucial role in supporting public health. However, the traditional drug-discovery paradigm is hindered by significant drawbacks, including high costs, lengthy development timelines, high failure rates, and limited output of new drugs. Recent advances in micro/nanotechnology, along with progress in computer science, have positioned microfluidics and artificial intelligence (AI) as promising transformative tools for drug development. Microfluidics offers miniaturized, multiplexed, and versatile platforms for high-dimensional data acquisition, while AI enables the rapid processing of complex, large-scale microfluidic data; together, they are accelerating a paradigm shift in the drug-discovery process. This paper first outlines the mainstream microfluidic strategies and AI models used in drug R&D. It then summarizes and discusses real-world applications of the integrated use of these technologies across various stages of drug discovery, including early drug discovery, drug screening, drug evaluation, drug manufacturing, and drug delivery systems. Finally, the paper examines the main limitations of microfluidics and AI in drug R&D and offers an outlook on the future convergence of these technologies.

药物研究与开发（R&；D）在支持公共卫生方面发挥着关键作用。然而，传统的药物发现模式受到重大缺陷的阻碍，包括高成本、冗长的开发时间、高失败率和新药产量有限。微/纳米技术的最新进展，以及计算机科学的进步，使微流体和人工智能（AI）成为药物开发的有前途的变革工具。微流体为高维数据采集提供了小型化、多路复用和通用的平台，而人工智能能够快速处理复杂的、大规模的微流体数据；它们共同加速了药物发现过程中的范式转变。本文首先概述了药物研发中主流的微流控策略和人工智能模型。然后总结并讨论了这些技术在药物发现的各个阶段的综合应用，包括早期药物发现、药物筛选、药物评估、药物制造和药物输送系统。最后，本文分析了微流体和人工智能在药物研发中的主要局限性，并对这些技术的未来融合进行了展望。

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引用次数: 0

Microcrack/Microscale Decorated Fiber-Based Electronics for Waist Rehabilitation 基于微裂纹/微尺度装饰纤维的腰部康复电子设备

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.07.004

Feiyu Tong , Jingmin Shi , Qi Jiang , Ming Li , Ruidong Xu , Ganghua Li , Yuanyuan Liu , Xinyu Zhang , Jinfeng Yang , Mingwei Tian , Yutian Li

Fiber-based strain sensors have emerged as revolutionary components in flexible electronics owing to their intrinsic compliance and textile compatibility, particularly in human-centric applications ranging from health diagnostics to motion tracking. While substantial progress has been achieved, a critical challenge persists in reconciling the contradictory demands of ultrahigh sensitivity and stable signal transmission through rational structural design. Herein, we develop dual-structure silver (Ag)/polyurethane (PU) fiber-based strain sensors (Ag@PU_x) via an integrated wet spinning and interfacial metal ion deposition (IMID) strategy. Notably, we propose a mechanical pre-stretching strategy that enables precise regulation of strain sensitivity and sensing range through controlled substrate deformation. Systematic characterization reveals that pre-stretched PU fibers form ordered microscale conductive networks, exhibiting exceptional electrical stability (conductivity (σ) = 1.9 × 10⁵ S·m⁻¹; the change in resistance value under external tensile force (ΔR)/the initial resistance of the sensor (R₀) < 0.03 under 360° torsional deformation) with a high quality factor (Q) of 10.1 at 50% strain. In contrast, non-prestretched counterparts develop microcrack-dominated architectures, achieving a high sensitivity (gauge factor (GF) = 7.7) through strain-induced crack propagation and a fracture strain exceeding 660%. A systematic investigation elucidates the underlying mechanisms behind these distinct sensing performances. The Ag@PU_x fiber-based electronics are capable of adapting to various tasks including human motion monitoring, voice recognition, and gesture recognition. Importantly, we developed the Ag@PU_x fiber-based electronics to monitor motion states while stably transmitting electrical signals. Ultimately, the Ag@PU_x show great promise in applications such as motion monitoring, waist rehabilitation, thermal management, electromagnetic shielding, and antibacterial deodorization.

基于纤维的应变传感器已成为柔性电子产品中的革命性组件，因为它们具有内在的遵从性和纺织品兼容性，特别是在以人为中心的应用中，从健康诊断到运动跟踪。虽然已经取得了实质性的进展，但通过合理的结构设计来协调超高灵敏度和稳定信号传输的矛盾需求仍然是一个关键的挑战。在此，我们通过集成湿纺丝和界面金属离子沉积（IMID）策略开发了双结构银(Ag)/聚氨酯（PU）纤维应变传感器（Ag@PUx）。值得注意的是，我们提出了一种机械预拉伸策略，可以通过控制基板变形来精确调节应变灵敏度和传感范围。系统表征表明，预拉伸PU纤维形成有序的微尺度导电网络，具有优异的电稳定性(电导率(σ) = 1.9 × 105 S·m−1；ΔR / R0 & lt;0.03%（360°扭转变形），在50%应变下的高质量因子(Q)为10.1。相比之下，未预拉伸的对应材料形成微裂纹为主的结构，通过应变诱导裂纹扩展实现高灵敏度（规范因子(GF) = 7.7），断裂应变超过660%。一项系统的研究阐明了这些不同传感性能背后的潜在机制。基于Ag@PUx光纤的电子设备能够适应各种任务，包括人体运动监测、语音识别和手势识别。重要的是，我们开发了Ag@PUx光纤电子设备，以监测运动状态，同时稳定地传输电信号。最终，Ag@PUx在运动监测、腰部康复、热管理、电磁屏蔽和抗菌除臭等应用中显示出巨大的前景。

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引用次数: 0

Revealing the Mechanisms of Compound Kushen Injection on Oxidative Stress Regulation in the Treatment of Radiation-Induced Lung Injury 揭示复方苦参注射液对放射性肺损伤氧化应激调节的作用机制

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.09.018

Boyang Wang , Defei Kong , Zhiru Yang , Jun Kang , Deyang Sun , Xiumei Duan , Jing Jin , Tingyu Zhang , Qingyuan Liu , Hui Yin , Shao Li

Radiation-induced lung injury (RILI) is a common complication of cancer radiotherapy, yet effective treatments remain elusive. Compound Kushen injection (CKI), a traditional Chinese medicine (TCM) formula, is widely used in clinical practice for treating radiation-related diseases and as an adjunct therapy for cancer and has demonstrated some effectiveness. However, the mechanisms underlying CKI intervention in RILI and its role in cancer adjunctive therapy remain unclear. In this study, we refined previous statistical approaches and successfully integrated quantitative data on the compounds in CKI. We constructed a network-based holistic target model and developed modular biological networks to explore the modular regulatory effects of CKI in RILI. Through this network-based analysis, we identified specific alkaloid components of CKI that contribute to its therapeutic effect in alleviating RILI. Furthermore, through transcriptomic analysis, we confirmed that oxidative stress plays a central role in the treatment of RILI by CKI. The modular regulatory effects of CKI have been validated in animal models of irradiation, demonstrating the ability of CKI to alleviate oxidative stress, reduce inflammation, regulate immune responses, and inhibit apoptosis. In addition, we demonstrated that nuclear factor erythroid 2-related factor 2 (NRF2) serves as a key mediator of the antioxidant effects of CKI. Matrine and sophoridine, representative alkaloids in CKI, exhibit binding interactions with NRF2. CKI promotes the nuclear translocation of NRF2, and NRF2 activates its downstream targets, such as heme oxygenase-1 (HO-1) and NAD(P)H quinone dehydrogenase 1 (NQO1), to suppress oxidative stress in RILI. This, in turn, inhibits the expression of inflammatory molecules, including interleukin (IL)-6, tumor necrosis factor (TNF)-α, and inducible nitric oxide synthase (iNOS), while promoting the activity of antioxidants such as superoxide dismutase (SOD) and glutathione peroxidase-4 (GPX-4), thereby exerting therapeutic effects on RILI.

放射性肺损伤（RILI）是癌症放疗的常见并发症，但有效的治疗方法仍然难以捉摸。复方苦参注射液（CKI）是一种中药方剂，被广泛应用于临床治疗辐射相关疾病和癌症的辅助治疗，并已显示出一定的疗效。然而，CKI干预RILI的机制及其在癌症辅助治疗中的作用仍不清楚。在这项研究中，我们改进了以前的统计方法，成功地整合了CKI中化合物的定量数据。我们构建基于网络的整体靶点模型，构建模块化生物网络，探索CKI在RILI中的模块化调控作用。通过这种基于网络的分析，我们确定了CKI的特定生物碱成分，有助于缓解RILI的治疗效果。此外，通过转录组学分析，我们证实氧化应激在CKI治疗RILI中起核心作用。CKI的模块化调节作用已在辐照动物模型中得到验证，表明CKI具有减轻氧化应激、减少炎症、调节免疫反应和抑制细胞凋亡的能力。此外，我们证明核因子红系2相关因子2 （NRF2）是CKI抗氧化作用的关键介质。苦参碱和槐碱是CKI中具有代表性的生物碱，它们与NRF2具有结合作用。CKI促进NRF2的核易位，NRF2激活其下游靶标，如血红素加氧酶-1 （HO-1）和NAD(P)H醌脱氢酶1 (NQO1)，从而抑制RILI的氧化应激。进而抑制白细胞介素(IL)-6、肿瘤坏死因子(TNF)-α、诱导型一氧化氮合酶（iNOS）等炎症分子的表达，同时促进超氧化物歧化酶（SOD）、谷胱甘肽过氧化物酶-4 （GPX-4）等抗氧化剂的活性，从而发挥对RILI的治疗作用。

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引用次数: 0

Global Top Ten Engineering Achievements 2025 2025年全球十大工程成就

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.11.004

Junzhi Cui, Jian-Feng Chen

引用次数: 0

Machine Memory Intelligence: Inspired by Human Memory Mechanisms 机器记忆智能：受人类记忆机制启发

IF 11.6 1区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering

Pub Date : 2025-12-01 DOI: 10.1016/j.eng.2025.01.012

Qinghua Zheng , Huan Liu , Xiaoqing Zhang , Caixia Yan , Xiangyong Cao , Tieliang Gong , Yong-Jin Liu , Bin Shi , Zhen Peng , Xiaocen Fan , Ying Cai , Jun Liu

Large models, exemplified by ChatGPT, have reached the pinnacle of contemporary artificial intelligence (AI). However, they are plagued by three inherent drawbacks: excessive training data and computing power consumption, susceptibility to catastrophic forgetting, and a deficiency in logical reasoning capabilities within black-box models. To address these challenges, we draw insights from human memory mechanisms to introduce “machine memory,” which we define as a storage structure formed by encoding external information into a machine-representable and computable format. Centered on machine memory, we propose the brand-new machine memory intelligence (M²I) framework, which encompasses representation, learning, and reasoning modules and loops. We explore the key issues and recent advances in the four core aspects of M²I, including neural mechanisms, associative representation, continual learning, and collaborative reasoning within machine memory. M²I aims to liberate machine intelligence from the confines of data-centric neural networks and fundamentally break through the limitations of existing large models, driving a qualitative leap from weak to strong AI.

以ChatGPT为代表的大型模型已经达到了当代人工智能（AI）的顶峰。然而，它们受到三个固有缺陷的困扰：过度的训练数据和计算功耗，容易发生灾难性遗忘，以及黑箱模型中逻辑推理能力的不足。为了解决这些挑战，我们从人类记忆机制中汲取见解，引入“机器记忆”，我们将其定义为通过将外部信息编码为机器可表示和可计算的格式而形成的存储结构。以机器记忆为中心，我们提出了全新的机器记忆智能（M2I）框架，它包括表征、学习和推理模块和循环。我们探讨了M2I的四个核心方面的关键问题和最新进展，包括神经机制、联想表征、持续学习和机器记忆中的协同推理。M2I旨在将机器智能从以数据为中心的神经网络的限制中解放出来，从根本上突破现有大型模型的限制，推动弱人工智能向强人工智能的质的飞跃。

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引用次数: 0