Concept for the Automatic Generation of Individual Test Sequences Verified by Artificial Intelligence Algorithms.

2021 ◽  
pp. 95-104
Author(s):  
Ralf Lutchen ◽  
Andreas Krätschmer ◽  
Hans Christian Reuss
Keyword(s):  
Artificial Intelligence ◽  
Automatic Generation ◽  
Individual Test

Automatic Story Generation

2021 ◽  
Vol 54 (5) ◽  
pp. 1-38
Author(s):  
Arwa I. Alhussain ◽  
Aqil M. Azmi
Keyword(s):  
Artificial Intelligence ◽  
Automatic Generation ◽  
Evaluation Methods ◽  
Extensive Study ◽  
Computational Creativity ◽  
Story Generation ◽  
To Receive ◽  
Shed Light

Computational generation of stories is a subfield of computational creativity where artificial intelligence and psychology intersect to teach computers how to mimic humans’ creativity. It helps generate many stories with minimum effort and customize the stories for the users’ education and entertainment needs. Although the automatic generation of stories started to receive attention many decades ago, advances in this field to date are less than expected and suffer from many limitations. This survey presents an extensive study of research in the area of non-interactive textual story generation, as well as covering resources, corpora, and evaluation methods that have been used in those studies. It also shed light on factors of story interestingness.

scholarly journals Artificial intelligence and copyright

2021 ◽  
pp. 15-22
Author(s):  
Daryna Prylypko
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Key Words ◽  
Automatic Generation ◽  
The Other ◽  
International Level ◽  
Human Agent ◽  
Foreign Countries ◽  
The One ◽  
Justice Practice

Key words: copyright, work, artificial intelligence, computer program In the article, the problemsof legislation of Ukraine regarding the issues of copyright on works created due to artificialintelligence were analyzed. Particularly, who is the owner of copyright ofworks created due to artificial intelligence. On the one hand, it could be a developer ofa computer program, from the other hand, it could be a client or an employer. Because,it could happen that there is a situation when robots created something newand original, e.g., how it happened with the project “New Rembrandt”. In this case,computers created a unique portrait of Rembrandt. And here is a question, where isin this portrait original and intellectual works of developers of these computers andprograms. In the contrast, this portrait could be created without people who developedspecial machines, programs, and computers. The article’s author proposes to addinto Ukrainian legislation with following norm: the owner of the copyright createddue to artificial intelligence should be a natural person who uses artificial intelligencefor these purposes within the official relationship or on the basis of a contract. In caseof automatic generation of such work by artificial intelligence, the owner of copyrightshould be the developer.Also, another question arises, particularly, who will be responsible for the damagecaused by the artificial intelligence. As an example, of the solution for this issue Resolution2015/2103 (INL) was given, where is mentioned that human agent could be responsiblefor the caused damage. Because, it is not always a developer is responsiblefor the damage.Also, the legislation and justice practice of foreign countries was explored. Theways of overcoming mentioned problems in legislation of Ukraine were proposed.Such as changing our legislation and giving the exact explanation in who is the ownerof copyright on works created due to artificial intelligence and in which cases this personcould become an owner of the copyright. However, probably, these issues shouldbe resolved at international level regarding globalization.

scholarly journals An Empirical Study on the Artificial Intelligence-Aided Quantitative Design of Art Images

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wen Zhang ◽  
Sang-Bing Tsai
Keyword(s):  
Artificial Intelligence ◽  
Network Model ◽  
Automatic Generation ◽  
Fine Art ◽  
Image Generation ◽  
Bilateral Filtering ◽  
Color Quantization ◽  
Main Research ◽  
Filtering Algorithm ◽  
Quantitative Design

This paper presents an indepth analysis and research on the quantitative design of fine art images through artificial intelligence algorithms. A CycleGAN-based network model for automatic generation of sketches of fine art images is constructed to extract the edge and contour features of fine art images. The network uses 512 × 1024 high-resolution art images as input and Pitchman as a discriminator. To further enhance the sketch generation effect, a bilateral filtering algorithm is added to the generator model for noise reduction, and then a K -means algorithm is used for color quantization to solve the problem of cluttered lines in the generated sketches. The experimental results show that the network model can effectively realize the automatic generation of art image sketches and can retain the detailed part of the costume information well. A rendering platform is built to realize the application of art image generation algorithms and coloring algorithms. The platform integrates the functions of image preprocessing, sketch generation, and sketch coloring, demonstrates the results of the main research content of this paper, and finally increases the interest of the system through the rendering function of the art image grid, which further improves the practicality of the platform.

scholarly journals An Iterative Polishing Framework Based on Quality Aware Masked Language Model for Chinese Poetry Generation

2020 ◽  
Vol 34 (05) ◽  
pp. 7643-7650
Author(s):  
Liming Deng ◽  
Jie Wang ◽  
Hangming Liang ◽  
Hui Chen ◽  
Zhiqiang Xie ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Model ◽  
Automatic Generation ◽  
Context Information ◽  
Chinese Poetry ◽  
Model Structure ◽  
Automatic Evaluation ◽  
Highly Qualified ◽  
Polishing Process ◽  
Global Context

Owing to its unique literal and aesthetical characteristics, automatic generation of Chinese poetry is still challenging in Artificial Intelligence, which can hardly be straightforwardly realized by end-to-end methods. In this paper, we propose a novel iterative polishing framework for highly qualified Chinese poetry generation. In the first stage, an encoder-decoder structure is utilized to generate a poem draft. Afterwards, our proposed Quality-Aware Masked Language Model (QA-MLM) is employed to polish the draft towards higher quality in terms of linguistics and literalness. Based on a multi-task learning scheme, QA-MLM is able to determine whether polishing is needed based on the poem draft. Furthermore, QA-MLM is able to localize improper characters of the poem draft and substitute with newly predicted ones accordingly. Benefited from the masked language model structure, QA-MLM incorporates global context information into the polishing process, which can obtain more appropriate polishing results than the unidirectional sequential decoding. Moreover, the iterative polishing process will be terminated automatically when QA-MLM regards the processed poem as a qualified one. Both human and automatic evaluation have been conducted, and the results demonstrate that our approach is effective to improve the performance of encoder-decoder structure.

scholarly journals Terms of use of judicial acts for machine learning (analysis of some judicial decisions on the protection of property rights).

2020 ◽  
Vol 4 (4) ◽  
pp. 102-114
Author(s):  
Ekaterina I. Alekseevskaya
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Property Rights ◽  
Private Property ◽  
Automatic Generation ◽  
Judicial System ◽  
Constitutional Court ◽  
Judicial Decisions ◽  
Judicial Practice ◽  
The Law

The subject of the article is some judicial acts on cases concerning protection of private property issued in Russia in recent years in the context of changes in the procedural legislation and legislation on the judicial system. The purpose of this article is to discover whether the current Russian judicial decisions may serve as input data for a machine learning algorithm in future. The main results, scope of application. The article presents an analysis of the changes in the Russian procedural law and in the regulation of the national judicial system in the recent years, which form new trends in judicial practice, according to the latest cases for the protection of private property in the courts. The author makes an analysis of the effectiveness of justice in providing recourse to private property violations in Russia. It is discovered whether the judicial protection has been substantially improved, following the promises of the Russian government. The article argues that these trends in judicial practice will negatively affect the automation of justice in the context of the nationwide digitalization of justice Such digitalization requires setting guidelines for the automated judicial decisions followed by the automated delivery of judicial documents. The methodology combines legal interpretation of judicial acts and Russian legislation comparative research, foresight and critical approach based on structured analysis, induction and deduction. Conclusions. There is a systemic deficiency in protecting private property in Russia, since neither the rules of civil and administrative proceedings, nor the constitutional control tools provide adequate protection on the matter. The recent relocation of the Constitutional Court of Russia from Moscow to St. Petersburg did not promote the judicial independence of the Court. On the contrary, the Constitutional Court, through formal excuses refrains from processing complaints on violation of private property rights and on the inefficiency of judicial procedures. The recent merger of the Supreme Arbitration Court of Russia and the Supreme Court of Russia has contributed to the uniformity of judicial practice. It violated the rights the owners of the shared premises in apartment buildings, but favored the beneficiaries of the management companies, which breach the owners’ rights. Judicial acts studied in this article prove their ineffectiveness in contributing to the quality machine learning for artificial intelligence required for the transition to automatic generation of blueprints and templates of court decisions. Analysis of judicial acts allows to conclude that they cannot serve now as a basis for machine learning of artificial intelligence. They cannot be systematized in databases even by the criterion of the law norms applied by the plaintiffs, since the courts evade the procedural obligation to explain why they reject the law norms that serve as the basis for a lawsuit or complaint, and apply completely different ones. These circumstances require the immediate response from the state authorities, including finding efficient ways to provide sustainable development of justice, i.e. ensuring the Rule of Law and access to courts, since otherwise the digitization of justice will lead to the automation of arbitrariness.

scholarly journals Exo Journalism: A Conceptual Approach to a Hybrid Formula between Journalism and Artificial Intelligence

2021 ◽  
Vol 2 (4) ◽  
pp. 830-840
Author(s):  
Santiago Tejedor ◽  
Pere Vila
Keyword(s):  
Artificial Intelligence ◽  
Case Studies ◽  
Professional Practice ◽  
Automatic Generation ◽  
Conceptual Approach ◽  
Digital Society ◽  
Automated Technology ◽  
Information Professionals ◽  
The Impact ◽  
Depth Interviews

The irruption of artificial intelligence (AI) and automated technology has substantially changed the journalistic profession, transforming the way of capturing, processing, generating, and distributing information; empowering the work of journalists by modifying the routines and knowledge required by information professionals. This study, which conceptualizes the “exo journalism” on the basis of the impact of AI on the journalism industry, is part of a research project of the Observatory for Information Innovation in the Digital Society (OI2). The results, derived from documentary research supported by case studies and in-depth interviews, propose that AI is a source of innovation and personalization of journalistic content and that it can contribute to the improvement of professional practice, allowing the emergence of a kind of "exo journalist", a conceptual proposal that connects the possibilities of AI with the needs of journalism’s own productive routines. The end result is the enhancement of the journalist’s skills and the improvement of the news product. The research focuses on conceptualizing a kind of support and complement for journalists in the performance of their tasks based on the possibilities of AI in the automatic generation of content and data verification.

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