Development Of AI Technology Research Articles

Optimization Strategies for Client Drift in Federated Learning: A review

With the development of AI technology, there is an increasing awareness and concern about data privacy, and training data is becoming more and more fragmented. To make better use of this distributed data while ensuring privacy, federated learning is proposed, which can federate multiple distributed devices to train a machine learning model and does not exchange the raw training data. A key challenge in federated learning is that the distribution of data across clients is heterogeneous, which leads to client drift, that is, local model updates toward local optimal solutions, resulting in performance degradation of the global model. To address this problem, many federated learning algorithms have been proposed. In this paper, we provide a review of existing federated learning optimization strategies. In our opinion, the existing optimization strategies for client drift can be roughly classified into the following two categories: model aggregation and model training. We introduce these two categories separately. Finally, we present our perspectives on the future development.

On the intelligent development of unmanned platforms in high-risk industries

With the development of AI technology and “New Infrastructure Construction, the intelligent development of unmanned platforms becomes significantly important for high-risk industries such as rescue activities in disasters, public emergencies, and emergency treatments. It will promote the safety and health of people and enhance capabilities for the national emergency and governance. This paper analyzes the current intelligent development of unmanned platforms for high-risk industries such as counter-terrorism, rescue activities in disasters, and emergency treatments. This paper summarizes the domestic and foreign current situations and development trends in four aspects: basic theories, key technologies, major equipment, and talent development. Based on the current situations, needs, and deficiencies of the intelligent development of unmanned platforms for high-risk industries of China, this paper proposes future challenges and problems for basic theories, key technologies, major equipment, and talent development. Moreover, this paper proposes high-level strategic planning and suggestions for the intelligent development of unmanned platforms for high-risk industries.

Construction of Special Program of Artificial Intelligence in Applied Universities of Finance and Economics

The development of AI technology has affected all walks of life in society, and then brought about the urgent demand for intelligent, compound and applied talents. Through the analysis of the current financial industry, finance and other industries, combined with the current situation of compound talent training in Financial Colleges and universities, the construction path of the "AI" special program in financial application colleges and universities is proposed, and the specific implementation plan of the course construction is described from the education objectives, curriculum objectives, teaching objectives, teaching plans and other aspects.

Research on APP Intelligent Promotion Decision Aiding System Based on Python Data Analysis and AARRR Model

With the development of AI technology and the current situation of the epidemic, online shopping is increasingly popular all over the world. The mobile phone terminals also occupy a larger share, and the use of various APPs has also emerged rapidly in line with the trend of the times. How big data technology is used to analyze the effective data generated by APPs? The paper conducts research from the following three aspects: (1)Finding out customer’s behavior patterns from the analyzed e-commerce data, and analyzing the reasons for customer churn rate and providing effective marketing strategies for merchants; (2) according to the time dimension, from different time dimension of customer behavior rules, find out customer purchase rules for merchants; (3) from the point of view of commodities, finding out customers’ preferences for different commodities, and give different marketing schemes for commodities with different preferences. Through the three aspects of the study, we use Python for data analysis, combined with AARRR model and traditional expert system, the arctic finally sets up an intelligent decision aid system recommended by APP, the system provides different marketing schemes for merchants. The experiment shows that through data analysis and simulation of the use of an APP, in the experimental environment, the APP can better serve customers under the same conditions, and the transaction rate has increased by 7.3%.

Suggestion of Building the AI Code of ETHICS through Deep Learning and Big Data Based AI

Purpose: Current social and technical issues related AI Ethics take many different forms. Therefore, efforts to make ethical guidelines to cope with these issues are actively being developed. However, most kinds of ethical guidelines present general ethical principles and take a deductive method of solving individual problems in ac-cordance. The purpose of this study is to propose creating ethical guidelines through an inductive method of deriving ethical principles based on ethical judgements on each individual AI-related cases. Method: At first, most representative cases of AI ethics-related guidelines would be investigated in domestic and international level, with collecting documents and literature review. After that, examine the commonalities and differences between cases as these basic data through comparative research methods. Accordingly, it would be revealed that each case is constituted by a deductive method. Finally, as an alternative to these me-thods, presenting the merits of establishing ethical principles related to AI through inductive cases and specific examples. Results: Most of the representative AI Code of Ethics that currently exist have the form of suggesting prin-ciples and then solving ethical problems by applying the principles to the actual events accordingly. This type of approach corresponds to the method of ethics which based on moral principles. However, complex and unpre-dictable problems are likely to arise when it comes to AI ethics. In order to solve these problems, it is necessary to extract the principles of the AI Code of Ethics by establishing and presenting ethical principles through re-searching and analyzing various individual events related to AI Ethics using deep learning and Big Data Based AI. Conclusion: The following effects can be achieved by using deep learning techniques and Big Data Based AI that contains Ethical Issues together with sound and desirable Moral Judgement on each case, to derive the principles of the AI code of ethics. First, it is possible to extract and secure Big Data as basic resource of present-ing Ethical Directions on various ethical problems arising in connection with the development of AI technology. Second, since the Ethical Principles as AI Code of Ethics are established based on empirical data, the validity of the principles can be secured. On the other hand, the AI Code of Ethics derived through deep learning based on such Big Data is likely to result in multiple tyranny or errors of majority due to certain limitations. So evaluation, verification and correction by Human Ethics Experts are essential to prevent these kinds of fault.

Artificial intelligence as a strategic instrument of economic development of Russia and improvement of its public administration

This article gives a comprehensive study of artificial intelligence technology as an instrument of economic development of Russia and improvement of its public administration. The study considers approaches to definitions, systematizes normative legal acts regulating the activities of economic and government entities that implement AI technology across the country, provides classification of AI technologies, gives additional market analysis. The study indicates key factors impeding gradual development of AI technology and its implementation within the government regulation process. This paper provides recommendations that help mitigate the impact of the accessed impeding factors and boost AI integration within the priority national economy sectors in order to achieve national and global development goals.

Using imaging to combat a pandemic: rationale for developing the UK National COVID-19 Chest Imaging Database.

The National COVID-19 Chest Imaging Database (NCCID) is a repository of chest radiographs, CT and MRI images and clinical data from COVID-19 patients across the UK, to support research and development of AI technology and give insight into COVID-19 disease https://bit.ly/3eQeuha

Freedom of Contract and Legal Issues in the Age of Artificial Intelligence

인공지능 기술의 발전은 사물을 인식하고 합리적으로 판단하여 목적적 의사를 자율적으로 결정하는 인간을 전제로 하는 계약의 근본 틀에 변화를 가져오고 있다. 특히, 인공지능 기술의 빠른 발전 속도를 고려하면, 이러한 변화는 앞으로 거세질 것이 분명하다. 따라서 인공지능 기술의 발전으로 야기될 수 있는 거래방식의 변화를 살펴보고, 우리 민법이 이러한 변화에 어떻게 대처해야 할 것인지를 고민할 필요가 있다. 구체적으로 인공지능의 등장으로 사적자치의 원칙이라는 민법의 기본원칙이 수정되고, 계약자유의 원칙에 따라 인정되던 계약형성력이 축소되어, 계약구속의 중요한 근거가 약화될 것이다. 또한, 디지털 세상이 내재하고 있는 변화의 신속성과 인공지능의 자율적이고 합리적인 판단력은 개별법률의 기본전제를 근본부터 흔들게 될 것이다. 그러나 인공지능에 관한 법률문제의 해결방안을 인공지능 자체에 대한 기술적 평가가 아닌, 인공지능을 거래나 생활에 개입시킨 이용자의 결정에서 찾는다면 인공지능 기술의 발전을 법률체계 내로 수용하여 문제를 한결 쉽게 해결할 수 있다. 인공지능의 이용결정을 통해 이용자는 그 계약 자체에 대해서도 최종 결정권자의 지위를 점하고, 그에 따른 책임을 지게 된다. 그러나 최종적으로 인공지능의 특성을 고려한 법개정이 필요해 보인다. 이때 원칙과 예외가 뒤바뀌어서는 안 될 것이며, 필요 최소한의 수정만이 이루어져야 할 것이다.The contract presupposes a free human being with reasonable judgment and purpose. Artificial intelligence(hereinafter “AI”) is changing the fundamental framework of this contract. As the technology of AI advances rapidly, these changes will be faster. To cope with the change, we must first look at the changes in contracting methods that can result from the development of AI technology. Specifically, the emergence of AI revises the principle of private autonomy. In addition, the power to make a contract, which was recognized by the principle of contract freedom, is reduced. Finally, the grounds for contract binding are weakened. Also, the rapid change of the digital world and the autonomous and rational judgment of AI will shake the basic premise of the current law. However, if the legal issue is identified in the decision of the user using AI, not the evaluation of the AI technology itself, the legal problem caused by the AI can be solved relatively easily. The decision to use AI makes AI users legally responsible. In spite of these solutions, it is necessary to finally amend the law considering the characteristics of AI. In this case, principles and exceptions should not be reversed. In addition, only the minimum necessary modifications should be made.

AI-Enabled Emotion Communication

With the development of AI technology, the application of AI will greatly change and influence people's daily lives. While AI technology brings great convenience to people's lives, people have shifted their focus from the physical world to the spiritual world, so there is an increasing demand for emotional services. As a result, emotional AI systems and emotional calculation are favored by many scholars nowadays. However, the existing emotional AI work mainly focuses on improving the accuracy of emotion recognition, lacking personalized emotional services for users. Therefore, in this article, the authors propose AI-EmoCom, which casts emotion as a communication medium in the network and makes the emotional communication system more intelligent by combining it with AI technology. We applied the AI-enabled emotional communication system to the field of unmanned driving, and proposed people-centered hybrid driving to reduce the incidence of traffic accidents to a greater extent. We also apply AI-enabled emotional communication to emotional social robots to provide users with personalized service emotion. Then the system architecture for the AI-enabled emotion communication is introduced in detail, and the no-tag learning model of dataset labeling and processing as well as the AI algorithm model for emotion recognition are elaborated in detail, and experiments are done to verify the interactive delay in the AI-enabled emotion communication system and accuracy of emotion recognition.

Discussion on the Development of Artificial Intelligence in Taxation

With the development of AI technology, a new forecasting and statistical model for tax auditing has been created. In recent years, thanks to breakthroughs in AI research, tax professionals have gained new analytical and statistical tools, providing convenience and improving efficiency. These tools have formed the basis for systematic frameworks that avoid the disorder and complexity of data processing and analysis in Excel spreadsheets. Additionally, AI provides simulated tax risks, which can help more complex human judgments to be made. AI can also aid detection of fraud, contributing to its supervision and monitoring by government. The development of AI continues, and its deployment has certain limits and risks that must be recognized.