The Next Era:Flourish of National Health Care & Medicine with the World Leading Artificial Intelligence

MODERN medical diagnosis and practice heavily rely on biological data and information from patients’ body.The progress of biomedical sensor,material and mathematical technology provided ever-increasing methods to gather data.While providing more choices and more comprehensive picture of patients’ conditions to doctors and practitioners,these progresses also require more labor efforts to read,analyze,and make decisions based on those data.It is very difficult for the medical human resources to grow at a speed that matches such need for diagnosis-related expert knowledge.The shortage of expertise has caused long waiting time for check report and fatal misjudged diagnosis in public health system,and it will compromise our ability to move towards a more precise,more personalized and more efficient future of medicine.

Research on the Construction Path of Ideological and Political Education for Postgraduates in the Era of Artificial Intelligence

Postgraduate ideological and political education is an important part of ideological and political education in colleges and universities.It is the core of implementing the party’s educational policy,comprehensively improving the quality of education,and building a modern socialist education power.In the era of artificial intelligence,innovate classroom education of ideological and political education for graduate students through intelligent network systems,natural language understanding systems,and knowledge processing systems;use intelligent search systems,symbol processing systems,and combined planning systems to deepen the communication links of graduate ideological and political education;through enhancing digital intelligence tools such as genetic algorithm,deep learning algorithm and artificial neural network algorithm to reconstruct the evaluation criteria of graduate ideological and political education is an important engine to promote the intelligent,contemporary and diversified development of graduate ideological and political education in my country.

Interaction and the Genesis of Experience: A Phenomenological Contribution for Meaningful Embodied Artificial Intelligence

In this article I will address the issue of the meaning of Embodied Artificial Intelligence(EAI)as it is configured today.My starting point is the refined interactive perspective on the semantics of EAI,as was recently suggested by Froese and colleagues.This perspective rests on the assumption that the concept of human bodily subjectivity must be extended to include meaning-making processes,which are enabled by advanced AI systems that may be incorporated in the human biological body.After having clarified the technical background,I will introduce the genetic component of the phenomenological method as a suitable tool to face the aforementioned issue.Towards this end,I will place the genetic method in the context of the so-called New Human-Machine Interaction(New HMI).I will further outline a genetic phenomenology of visual embodiment,suggesting a futuristic application based on the thesis of the“technological supplementation of phenomenological methodology”through the synthetic method.The case at stake is that of patients with a severe clinical picture characterised by the loss of corneal function,who in the near future could be treated with synthetic corneal prosthetic implants produced by a 3D bio-printing process by using an advanced EAI technique.I will conclude this article with a brief review of the main problems that still remain open.

Analysis on the Development of Cigarette Packaging in the Era of Intelligence

China is one of the biggest countries in cigarette production and sales,therefore it is important to improve the quality and efficiency of cigarette production.As cigarette packaging is an important part in cigarette production,therefore,it is important to strengthen research on improving the quality of cigarette packaging.This article summarizes the development process of cigarette packaging in China,introduces the development of printing technology in the era of intelligence,summarizes the application of printing technology in cigarette packaging,analyzes and explores the development trend of cigarette packaging in the era of intelligence,with the hope to provide reference for practitioners.

Heading toward Artificial Intelligence 2.0

With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence （AI） has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage： AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the develoDment of Al 2.0 are given.

Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.

Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network

With the continuous development of social economy,science and technology are also in continuous progress,relying on the Internet technology of big data era has come in an all-round way.On the basis of the development of cloud computing and Internet technology,artificial intelligence technology has emerged as the times require.It also has more advantages.Applying it to computer network technology can effectively improve the data processing efficiency and quality of computer network technology,and improve the convenience for people’s life and production.This paper studies and analyzes the practical application requirements of computer network,and discusses the application characteristics and timeliness of artificial intelligence technology.

Human-Machine Shared Lateral Control Strategy for Intelligent Vehicles Based on Human Driver Risk Perception Reliability

Intelligent vehicle(Ⅳ)technology has developed rapidly in recent years.However,achieving fully unmanned driving still presents numerous challenges,which means that human drivers will continue to play a vital role in vehicle operation for the foreseeable future.Human-machine shared driving,involving cooperation between a human driver and an automated driving system(AVS),has been widely regarded as a necessary stage for the development of IVs.Focusing onⅣdriving safety,this study proposed a human-machine shared lateral control strategy(HSLCS)based on the reliability of driver risk perception.The HSLCS starts by identifying the effective areas of driver risk perception based on eye movements.It establishes an anisotropic driving risk field,which serves as the foundation for the AVS to assess risk levels.Building upon the cumulative and diminishing effects of risk perception,the proposed approach leverages the driver's risk perception effective area and converts the risk field into a representation aligned with the driver's perspective.Subsequently,it quantifies the reliability of the driver's risk perception by using area-matching rules.Finally,based on the driver’s risk perception reliability and dif-ferences in lateral driving operation between the human driver and the AVS,the dynamic distribution of driving authority is achieved through a fuzzy rule-based system,and the human-machine shared lateral control is completed by using model predictive control.The HSLCS was tested across various scenarios on a driver-in-the-loop test platform.The results show that the HSLCS can realize the synergy and complementarity of human and machine intelligence,effectively ensuring the safety ofⅣoperation.

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence:mechanisms and applications of cognition,management,and control for complex systems

In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.

Swarm Intelligence Research:From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm Intelligence

Swarm intelligence has become a hot research field of artificial intelligence.Considering the importance of swarm intelli-gence for the future development of artificial intelligence,we discuss and analyze swarm intelligence from a broader and deeper perspect-ive.In a broader sense,we are talking about not only bio-inspired swarm intelligence,but also human-machine hybrid swarm intelli-gence.In a deeper sense,we discuss the research using a three-layer hierarchy:in the first layer,we divide the research of swarm intelli-gence into bio-inspired swarm intelligence and human-machine hybrid swarm intelligence;in the second layer,the bio-inspired swarm intelligence is divided into single-population swarm intelligence and multi-population swarm intelligence;and in the third layer,we re-view single-population,multi-population and human-machine hybrid models from different perspectives.Single-population swarm intel-ligence is inspired by biological intelligence.To further solve complex optimization problems,researchers have made preliminary explor-ations in multi-population swarm intelligence.However,it is difficult for bio-inspired swarm intelligence to realize dynamic cognitive in-telligent behavior that meets the needs of human cognition.Researchers have introduced human intelligence into computing systems and proposed human-machine hybrid swarm intelligence.In addition to single-population swarm intelligence,we thoroughly review multi-population and human-machine hybrid swarm intelligence in this paper.We also discuss the applications of swarm intelligence in optimization,big data analysis,unmanned systems and other fields.Finally,we discuss future research directions and key issues to be studied in swarm intelligence.

Implementation of Strangely Behaving Intelligent Agents to Determine Human Intervention During Reinforcement Learning

Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their environments.However,simulations of different learning environments in previous research show that after millions of timesteps of successful training,an intrinsically motivated agent may learn to act in ways unintended by the designer.This potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real world.We investigated this topic by using Unity’s MachineLearningAgent Toolkit(ML-Agents)implementation of the Proximal Policy Optimization(PPO)algorithm with the Intrinsic Curiosity Module(ICM)to train autonomous exploring agents in three learning environments.We demonstrate that ICM,although designed to assist agent navigation in environments with sparse reward generation,increasing gradually as a tool for purposely training misbehaving agent in significantly less than 1 million timesteps.We present the following achievements:1)experiments designed to cause agents to act undesirably,2)a metric for gauging how well an agent achieves its goal without collisions,and 3)validation of PPO best practices.Then,we used optimized methods to improve the agent’s performance and reduce collisions within the same environments.These achievements help further our understanding of the significance of monitoring training statistics during reinforcement learning for determining how humans can intervene to improve agent safety and performance.

论智能时代的学生主体性及其培育

如何培养学生合理使用技术并与之共生的能力,同时警惕学生被机器异化而丧失主体性是中国教育现代化进程中需要关注的问题。智能时代,人机协同的教学境遇促发学生主体性的后人类转向,使之呈现出增强扩展、隐性让渡、虚化延展与封闭趋同的新特点。教学作为学生主体性发展与培育的重要活动,遭遇着何以为教的知识困境、人师角色的缺失困境、虚实空间的错位困境及教学艺术的遁隐困境。培育学生主体性需要从课程知识的重新厘定、人师角色的回归进化、虚实空间的精准定位以及教学技术与教学艺术的调和等方面来纾解这些困境。

智慧教育时代高校教师数字化教学能力提升的挑战与应对

在智慧教育时代背景下,数字技术已迅速融入高等教育,未来高等教育智慧化转型成为必然趋势。教师是教育改革和发展的第一资源,未来高等教育的智慧化转型对高校教师教学能力提出了更高的要求。高等教育智慧化转型以其独特的优势从教学技术知识、教学法知识、学科内容知识三个方面助力高校教师教学能力提高。同时,高校教师也将面临教育教学意识数字化转型、教育教学技术知识与技能数字化转型、教育教学数字化应用能力提升、数字化融入教师专业发展等诸多挑战。应通过重塑教师教育教学价值观、夯实教师数字教育教学知与能、提高教师数字技术应用能力、提升教师数字化专业发展能力和激发教师的内在驱动力等措施提高高校教师的数字化教学能力。

数智时代人文社科数据资源开发利用的跃迁:从观念到行动

近年来数据资源开发利用的热潮已然在人文社科领域扩散开来,人文社科的数据资源观正在从传统的有限样本资料、“小数据”向大数据、智慧数据转变。针对当前人文社科数据资源开发利用仍然存在的“保护”“深闺”“孤岛”“同质”“展示”现象,本文构建了以主体层、内容层、保障层为核心的人文社科数据资源开发利用路径框架:主体层强调顶层规划主体、建库主体、数据用户之间的协同合作;内容层凸显逻辑维、资源维、方法维、验证维的组合路径;保障层涉及政策法规、资金项目、人才资源、文化氛围等保障措施。面向未来,人文社科数据资源开发利用需要积极打造人文社科数据资源“治理术”,在基本理念上需要从“资源基础论”向“治理能力论”转变,在具体行动上可从数据基础设施体系搭建、多学科数据资源共生共长机制构建、数据资源产权与安全有效保护、基于数据资源的服务链建构等方面着力推进。图1。参考文献15。

数智时代我国高等教育评估体系的转型与重构

数智时代我国高等教育的转型呼唤高等教育评估的变革。从内涵维度透视,高等教育评估的目的由单一价值判断转向多元智能优化,评估的尺度由单视域及时反馈转向多视域实时呈现,评估的模式由数据集中密集转向区块互联分布。从功能维度透视,全息评估支撑多元主体从认识价值上升为“共创价值”,人工智能驱动主管部门从被动应对决策上升为主动“预警预测”,人机互动牵引教育教学质量从持续改进上升为“提质增强”。建构新型高等教育评估体系须秉持“以评促强、争创一流”的发展理念,探索“平台化”协同慧治的治理模式,创造“教育评估智能体”的超级生态,持续系统提升高等教育质量,服务于教育强国建设。

智能时代大学生劳动教育价值重塑与实践路径

“劳动”是人类文明发展的最重要与最基本的方式,是提升国民经济的强大动能。纵观当前,以智能技术为主体的新型劳动形式,不仅给传统劳动带来挑战,也冲击了人们传统的劳动理念。大学生劳动教育应顺应时代发展潮流,充分借助和发挥智能设备、智能技术、智能手段,使劳动教育拥有全新的育人形态,促进学生德智体美劳全面发展。结合智能时代对人类劳动的影响,明确劳动教育价值重塑的内容,分析劳动教育的问题,提出科学合理的劳动教育实践路径。

新时代 新征程 新伟业——大阅读时代图书馆高质量发展思考

结合近年来国内外图书馆的发展理念与创新实践,从形势与任务、使命与愿景、理念与范式、战略与路径4个维度,对大阅读时代图书馆高质量发展这一议题进行阐述与思考。

中国式现代化数字文化强国建设:理论逻辑与革新路径

伴随数智技术的迭代,我国文化建设开启了建构文化自信和文化强国、以“中国式”“现代化”“数字化”为关键词的发展演进之路。关于文化强国的研究命题已引起学界高度关注,但缺乏立足数字文明时代中国式现代化大背景的系统考量。一方面,亟须阐明中国式现代化数字文化强国的生成逻辑与理论蕴涵,系统构建数字文化强国发展框架。其中,意识形态领导力、制度前瞻力、文化自信力、文化科技创新力、文化产业竞争力是该框架的主要构成要素,推进中国式现代化数字文化强国建设应立足彰显思想引领、精神引导、文化自强的价值内核,实现由文化自信到文化自强,最终建成数字文化强国的战略目标。另一方面,应深刻把握系统科学理论的涌现性、非线性、突变性、主体能动性、复杂性的价值内核,从思想引领、制度前瞻、文化自信、科技赋能、产业现代化五个维度协同构建中国式现代化数字文化强国建设的革新路径。

智能时代在线课程的应然样态、实然困境与实践路向

人工智能技术的每一次迭代更新都冲击已然形成且较为稳定的在线教育系统,衍生出新的在线教育实践形态。未来在线课程将呈现以智能素养为核心的智能育人体系、课程资源定制化供给、AI智适应导向的在线学习活动、凸显深度态势感知的人机融合、全流程精细化在线课程评价的应然样态。实践中,课程用户难留住、课程质量难提升、智能交互薄弱以及科技伦理引发争议等现实困境都阻碍着在线课程的发展。为推动智能时代在线课程持续发展,应当关注用户体验、提升智能在线课程质量,促进技术融创、建设智能在线课程体系,增强智能交互、探索智能在线课程模式,坚守伦理底线、全面提升智能监管水平,促进新一代人工智能技术与在线课程的深度整合。

数智时代情报学学科体系构建

[目的/意义]在一级学科更名的转型期,为了持续推进我国情报学研究的守正与创新,需要重新构建数智时代情报学学科体系,以便服务于总体国家安全战略和发展战略。[方法/过程]以转型前后的情报学研究生教育为出发点,理解数智时代的特征和“三大体系”的内涵。探讨国际情报学和中国情报学的起源,梳理我国情报学的英文范式和中文范式,将信息链原有的线性结构改造成环形结构,提出情报学的“信息·情报一体化范式”。辨析几个容易混淆的关键英文术语,澄清某些模糊认识。回顾我国情报学学科体系研究的几种观点,构建数智时代情报学学科体系。[结果/结论]划分出广义情报学和狭义情报学,以便恰当处理军用情报学和民用情报学的关系。明确了英文语境下Information Science与中文语境下“情报学”的异同。一体化范式在一定程度上融合了Information范式与Intelligence范式。重新构建的分层式同心圆形结构的情报学学科体系,较为完整地体现数智时代情报学学科体系的全貌。