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Copyright of Lexikos is the property of Bureau of the Woordeboek van die Afrikaanse Taal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper aims to provide an image of the future of teaching and learning in the context of artificial intelligence transforming various industries, including sports, education, and construction. Its place in education is a frequently discussed topic. While some argue that artificial intelligence will revolutionize education, others worry that it will take over to the harm of educators and students. Though robotics in the classroom is still a ways off, artificial intelligence is finding its way into the classroom. AI has the power to improve teaching and learning methods, solve some of the largest issues facing education today, and hasten the achievement of inclusive and equitable quality education. In addition to delivering artificial intelligence courses, EdTech businesses are increasingly using eLearning solutions to personalize learning experiences, pinpoint knowledge gaps, and give focused feedback. Also, AI-driven education is upending conventional teaching methods and influencing how this field will use technology in the future. With the use of complex algorithms and massive data sets, artificial intelligence solutions for education may provide a lot of advantages, yet as with the use of artificial intelligence in any context, there are significant ethical considerations which are a hot topic of discussion in the technology world and beyond, and the majority of university degree programs are including courses on AI ethics in their curricula. Therefore, the paper presents the benefits of AI in the classroom, such as engagement and assistance for students, assessment and evaluation, and individualized learning but also about the difficulties and worries associated with AI in education, including prejudice and privacy issues, as well as the moral issues raised by AI-powered learning. It also discusses the possible effects on the educational system and how students are trained for the workforce of the future as potential applications of AI in education are explored.

Abstract Money laundering and financial crimes pose a significant threat to the integrity and stability of South Africa’s financial system. This paper explores the application of artificial intelligence (AI) to detect and prevent money laundering in South African banking institutions. Through the implementation of big data technologies and data processing analytics, AI can enhance the detection and prevention of money laundering activities in South Africa’s banking sector. AI can be harnessed to improve the detection of suspicious activities, enhance accuracy of financial intelligence and adapt to evolving money laundering techniques. The paper also examines the benefits and challenges of implementing AI as an anti-money laundering (AML) measure in the South African banking sector. These include the need for quality data, integration with existing systems, regulatory compliance and ethical considerations. The paper further highlights the potential of AI in transaction monitoring, customer due diligence, outcomes-based risk assessment, and improved detection of suspicious transactions by analysing how AI can enhance the effectiveness and efficiency of AML measures. The importance of coordination between banking institutions, regulatory authorities and law enforcement bodies is also highlighted as an important component of leveraging AI to combat money laundering and related financial crimes in South Africa’s banking sector.

Copyright of Journal for Religion in Education / Religionspädagogische Beiträge is the property of Arbeitsgemeinschaft Katholische Religionspadagogik & Katechetik (AKRK) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of GMS Medizin-Bibliothek-Information is the property of German Medical Science Publishing House gGmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The generation of printable shellcode is an important computer security research area. The original idea of the printable shellcode generation was to write a binary, executable code in a way that the generated byte code contains only bytes that are represented by the English letters, numbers and punctuation characters. In this way unfortunately only a limited number of CPU instructions can be used. In the originally published paper a small decoder is written with instructions represented by printable characters and the shellcode is decoded on the stack to be executed later. This paper, however describes a proof of concept project, which converts the source code of a full assembly program or shellcode to a new source code, whose compiled binary code contains only printable characters. The paper also presents new, printable character implementation of some CPU instructions. [ABSTRACT FROM AUTHOR]

AI-based chat agents within educational settings present a promising pathway for bolstering collaborative learning (CL), especially in the sphere of English as a Foreign Language (EFL). This paper investigates the evolving role of chat agents based on Artificial Intelligence (AI) and Large Language Models (LLM), notably ChatGPT, in the landscape of CL specific to EFL. The primary aim is twofold: firstly, to discern the productive and unproductive applications of ChatGPT in a CL environment, and secondly, to investigate approaches for harnessing ChatGPT to amplify productive CL experiences in EFL contexts. We present a literature review addressing the main objective of this paper, i.e., the exploration of the productive and unproductive uses of ChatGPT for CL in the EFL context. The findings aim to provide insights into the capabilities and limitations of ChatGPT in fostering language skills, enhancing communication competence, and encouraging cooperative learning strategies among EFL learners. This present paper delineates approaches and possible pitfalls when employing AI chat agents in language learning, attempting to bridge the divide between AI technology and instructional design, aiming to facilitate a more informed and efficacious utilisation of AI within collaborative EFL learning environments.

This paper considers the transfer of approaches from the field of to the field of to be used in decision support systems. The most relevant of the developed approaches will be roughly introduced and it will be considered how these approaches can be applied in medical informatics in the context of decision support systems. Moreover, it will be considered which of the approaches are eligible in this context. Apart from placing the approaches in the context of decision support systems, the paper thereby also provides an example for the interplay of different fields of research.

Artificial intelligence (AI) and robotics have emerged as game-changing technologies with the potential to revolutionize the healthcare industry. In the context of hospitals, their integration holds the promise of not only improving patient care but also driving competitive advantage and fostering sustainable development. This review paper aims to explore and evaluate the impact of AI and robotics applications on attaining competitive advantage and promoting sustainable developmenospitals, examines the current landscape of AI and robotics adoption in healthcare settings and delve into their specific applications within hospitals, including AI-assisted diagnosis, robotinitoring, and data analytics. A key finding is the insufficient use of KI to date in terms of promoting sustainable development in hospitals. Furthermore, attempts to analyze the potential benefits and challenges associated with these technologies in terms of enhancing patient outcomes, operational efficiency, cost savings, and differentiation from competitors. Drawing upon a comprehensive review of the existing literature and case studies, this paper provides valuable insights into the transformative potential of AI and robotics in hospitals.

Copyright of Annales de la Faculté de Droit d'Istanbul is the property of Annales de la Faculte de Droit d'Istanbul and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of e & i Elektrotechnik und Informationstechnik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial Intelligence and Language Technologies in the Field of Translation The present paper deals with the opportunities which language technologies and artificial intelligence might offer for translation professionals. The paper also examines and elucidates that these technologies might contain possible problems, hurdles and obstacles. But the researcher reinforces that they also possess the necessary skills, competencies and prerequisites for the successful implementation and use of these technologies as illustrated in the Literature Review and Discussion parts of this research. It has also been shown that the successful implementation of such tools requires both institutional and technical prerequisites. A not inconsiderable problem, however, is the question of the what extent to which and whether the significance of the digital translator can also be adequately illustrated and clarified in the non-institutional private sector. Current developments in this respect unfortunately tend to point to the opposite, i.e. to the degradation of his role to a mere "helper" of the machine that (apparently) does most of the translation work. Translators, then, will ultimately only be able to truly benefit from language technology and artificial intelligence if their status is not further compromised as a result. It is not very helpful if productivity and speed can be increased, but in inverse proportion to this, the fees constantly decrease, because it is made to appear that the computer is now doing most of the work. The end result of this development would be the digital slave rather than the highly professional digital language mediator. The paper projects that language technologies and artificial intelligence potentially offer benefits in the sense that they promote a better understanding and functioning of the symbiosis between humans and machines through the automation and streamlining of certain language-related workflow processes, i.e., a set of tasks that can be performed primarily - or even entirely - through workflow automation and with the help of content management software. Through the various past research on the subject and through secondary data analysis it has been analysed and stated in the paper that the potential acceleration of work processes improves overall efficiency by requiring less time to complete the same tasks. Therefore, this study evidently establishes the argument that artificial intelligence allows human actors to focus on more meaningful tasks associated with quality control, while routine and especially technical tasks are delegated (for the most part) to the machine. This also leaves more time for creative aspects. Artificial intelligence and language technology are not only relevant for translating, but also for interpreting, even if progress in this area is still somewhat slower and a paradigm shift has yet to occur. In this regard, conference interpreting is of particular interest. Problematically, the relevant software has so far lacked the cognitive, cultural, intellectual, and emotional skills that inevitably underlie qualitatively responsive interpretation. But at least it is possible to improve the interpreter's preparation for a meeting or conference. The relevant tools have so far only a supporting role to play. Language technologies and artificial intelligence potentially offer benefits in the sense that they promote a better understanding and functioning of the symbiosis between humans and machines through the automation and streamlining of certain language-related workflow processes, i.e., a set of tasks that can be performed mainly - or even entirely through workflow automation and with the help of content management software. Further development of artificial intelligence, machine translation has recently made significant progress. Nevertheless, it is common practice to first subject the machine-translated text to review or proofreading by a human translator. Post-editing is the process of using a machine-translated text as a basis and having it improved by a human translator. This means that the human translator ultimately creates the final translation.

Copyright of e & i Elektrotechnik und Informationstechnik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Formalization of natural language metaphors is a notorious problem in artificial intelligence and in other overlapping domains. It is semantic vagueness that makes metaphors resistant to formulaic or algorithmic descriptions. Great effort has been invested into modeling metaphors computationally but the issue remains methodologically uncertain and needs further research. This paper works on a practical solution to the problem how metaphorical meaning can be represented in a way suitable for computation. The research agenda of this paper is interdisciplinary; it brings together an algebraic heuristic-driven theory for metaphors developed in artificial intelligence and an applied theory of meaning that comes from cognitive linguistics. This agenda postpones theoretical speculation and argument and is solely solution-focused, which contributes to the value of this paper’s attempt to bridge the cognitive science disciplines whose compatibility, though declared, is seldom demonstrated in a piece of practical research. This paper works with metaphors of human emotions that are linguistically manifested in modern English discourse. Emotions by virtue of their ineffability as qualia are rich in metaphorical conceptualizations and serve the research agenda well. This paper in a meaningful way exposes and ranks designated properties of the FEAR, SADNESS, HAPPINESS, and RELAXATION/SERENITY concepts and arranges these properties into general-purpose ontologies that explicitly specify metaphorically preferred emotion conceptualizations and are good candidates for computation. In prospect, this paper will account for some theoretical aspects of the research and probe the algorithmic and repetitive nature of schemas that license metaphorical expressions in natural language.

Copyright of Mitteilungen der DMV is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the authors seek to critically questioning the relationship between technology and the mind, machine and man, we also try to understand the medium of the Internet, its nature and the way inwhich its integration into everyday life is changing everyday life. The For 30 years, Internet has been a technology, but also a medium of mass communication in society, but the discussions about it are mostlyreduced to either laud of technology or skepticism, which, as Silva Vaidhyanathan (2018) says, are representing those named as „‘orthodox’ media ecologists“. Therefore, in this paper, we are trying to understand the relationship between technology (media) and the mind (man), starting from the observations made by Mumford, Nietzsche, McLuhan, Freud, to the contemporary thinking of McChesney, Carr, Keene, Vaidhyanathan, Searl. We are considering the ways in which the previousmedia, including speech, letter, photography, were changing society and human needs, but also new, changed patterns of behavior in everyday life, which were partly created due to our use of the dominant technology of contemporary age. We also study the source of man’s need for new technologies, inventions, machines, his desire for the control of nature and technique, which, seemingly, is easily transformed into the control of the man himself. In this paper we do not give the final answers to the growing problems and issues of today’s networked and technologized world, but we are dealing with reflections on the development of the Internet, communication technologies and artificial intelligence.

This paper reviews the current research on AI-assisted language education (AILE). AI has greatly influenced education, especially language learning. AILE, an interdisciplinary field combining AI technology and language education theory, aims to improve foreign language learners’ experiences through personalized, interactive, and collaborative learning. This review classifies AILE research into four key domains: language-specific applications, comprehensive teaching modes, new educational ecosystems, and identification technology integration. It analyzes the strengths, weaknesses, opportunities, and challenges of AILE. The paper emphasizes the importance of ethical considerations and data quality in AILE endeavors. While acknowledging the achievements and potential of AILE, the review suggests future directions, promotes interdisciplinary collaboration, and highlights the need for empirical studies for an effective and ethical integration of AI in language education.

Although the accounting definition of assets contemplates intangible, abstract assets such as those embodied in intellectual property (IP), South African company law largely views IP as a legal and not a business asset. This paper tentatively suggests an approach that uses artificial intelligence (AI) to mitigate weaknesses in the South African patent law relating to the absence of patent searches and examinations. It is hoped that using AI will enable the filing of quality patents that satisfy the prescribed patentability criteria. High-quality patents will allow companies to accumulate patents as corporate assets. The approach is based on the algorithmic use of AI technologies such as machine learning, natural language processing, deep learning alongside the Internet of Things, and IP analytics to strengthen South Africa’s IP system and create asset value for corporations. The paper recommends using the proposed AI technologies by companies and the Patents Office to enable the filing of high-quality patents, which will lead to the accumulation of corporate assets in the form of patents. The methodology is doctrinal, and the paper relies on recent literature on IP and AI, South African law, case law and examples drawn from studies conducted in other countries.

Copyright of Mitteilungen der DMV is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The most important property, a distinctive feature of any intelligent system, is its decision-making ability. In this case, the more complex the problem to be solved, the more and more diverse the initial data, and the more critical it is that the decision to be made was comprehensively considered and evaluated. In many cases, simultaneously arriving various initial data, if considered separately, and decisions based on such consideration lead to completely different results, often contradicting each other. Therefore, in the process of development and implementation of artificial intelligence (AI), it is especially important to investigate the “mechanism” of decision-making in conditions of the inconsistency of incoming initial data and the need to establish some generalizing rule, according to which it is possible to find a harmonizing solution taking into account various influencing factors. It is evident that when establishing the rules of decision-making, it is necessary to strive for a “positive” result from the point of view of the problem being solved. This undoubtedly requires analyzing the consequences of the decision made in a set time scale, which can be provided by appropriate feedback that will allow us to make the necessary corrective actions. Artificial intelligence in modern forms of practical realization has, as a rule, a digital embodiment. It should be taken into account that the digital representation of data inevitably shows an inaccurate display of initial values when processes of a continuous nature are considered and analyzed. Since a digital model has certain limitations and characteristic properties when analyzing and processing initial data, it is logical to assume that for this reason, there can be some general approach, some general rule, according to which a decision is made in the conditions of diverse initial data and the need to take into account the relevant consequences after the decision is made. This paper attempts to find a decision-making mechanism, harmonizing it according to the incoming external and available internal input data.

In today's professional communication, a constant expansion of vocabulary is necessary to keep up with developments in technology and science. This paper looks at the current topic of artificial intelligence in relation to applications such as ChatGPT and chatbots. The investigation will also explore the potential of artificial intelligence in promoting and supporting linguistic skills. Additionally, the discussion will cover the implementation of these AI tools into foreign language curricula and classroom practices. Specific requirements for teachers and students are addressed under the aspect of future competencies, which represent a particular challenge given the high speed of diverse developments. This study contributes to the ongoing discussion regarding the role of artificial intelligence in higher education. Overall, this evaluation offers insights into a highly topical issue of AI application that will significantly influence linguistic and pedagogical practice in the future.

This paper explores the evolving perception of artificial intelligence (AI) systems in our increasingly AI-driven world, focusing on conversational AI or chatbots. With the rise of human-like robotic AI systems, there is a growing need to understand the identity these machines assume as they take on roles previously reserved for humans, such as caring for the elderly and educating children. The central thesis posits that comprehending the identity of such AI systems necessitates considering the aspect of our own identity that we shape and project onto them in our interactions with these systems. In an era defined by AI, these inquiries into identity and AI-human interactions are of paramount importance and are also vital for the very development of AI.

Copyright of Medien & Kommunikationswissenschaft is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bibliotheksdienst is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial Intelligence (AI) has already become a ubiquitous and autonomous force transforming our society and how humans interact with the world around them and each other. The staggering development and widespread of AI technology in the last decade raise debates on its evolution potential and social anxiety concerns about its detrimental effects. Techno-optimists expect AI to evolve into a sentient and conscious entity, reaching and surpassing humanlevel and thus challenging our understanding of the world and the fundamental principles of our society. This paper provides theological reflections on AI evolution and its effects on society and Christian spiritual life. It discusses the risks of AI hindering man’s spiritual ascent towards God by autonomously shaping man and society in its image, as expressed by advocates of technological determinism. Finally, it proposes an authentic and liberating Christian viewpoint on AI and today’s disruptive technologies by employing a patristic perspective.

This paper explores the evolving role of teachers and literary translators in the era of artificial intelligence and machine translation and addresses the challenges encountered in literary translation. It focuses on achieving a balance between human expertise and machine power to ensure faithful translations of literary works while preserving their inherent artistic value. The study analyses four translations of an excerpt from the short story “Lake Como” by Serbian writer Srđan Valjarević. These translations, from Serbian to English, were conducted in groups by third-year Anglistics students at the Faculty of Philology, Sinergija University in Bijeljina, whose native language is Serbian. The quality and accuracy of the translations were assessed, accompanied by detailed justifications of our preference judgments. A comparison was made between our assessments and those generated by Chat GPT-3, aiming to provide insights into the advancements made by AI in the realm of literary translation. This comprehensive evaluation of translations, encompassing both human translators and AI-powered language models (LLMs), offers a deeper understanding of the specific strengths and weaknesses exhibited by LLMs in the context of literary translation. Through this human evaluation process, we strive to shed light on the specific areas where LLM translators excel and identify the challenges they are still facing. The findings contribute to a deeper understanding of AI's impact on literary translation and pave the way for future research and advancements in this area.

The issue of the "Mitteilungen der DMV" (Announcements of the German Mathematical Society) from March 1, 2023, contains various articles on mathematical topics. One article by Jessica Wynne deals with the beauty of mathematical chalkboard images. The president of the DMV, Joachim Escher, gives a greeting. Other articles discuss topics such as the Tilings Encyclopedia, the development of ChatGPT in AI research, and mathematics in the digital society. There is also an article on the geometry of negotiation tables and a contribution on life and work in Germany from an external perspective. The position paper by DMV, GDM, and MNU on combating the shortage of mathematics teachers is also presented. The issue concludes with information about new members, appointments, promotions, and the imprint. [Extracted from the article]

This article is both an editorial introduction to the guest-edited special issue of JoSTrans on Translation Automation and Sustainability, and a position paper in which we propose a model for evaluating the sustainable use of automation technology in translation and beyond. As grounding notions, the article reviews definitions of automation and considers the urgency of sustainability. Thereafter we propose an adaptation of Elkington’s (1997) triple bottom line, giving equal weight to evaluation based on people, planet, and performance, describing each of these elements in turn. Finally, we introduce the articles from this special issue, in which authors describe various aspects of automation technology in translation with a focus on sustainability.

Copyright of Wirtschafts- und Sozialwissenschaftliches Institut Mitteilungen is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Wirtschafts- und Sozialwissenschaftliches Institut Mitteilungen is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this article. The aim of the article is to analyze selected issues related to artificial intelligence and its development, particularly its impact on the financial market, taking into account the opportunities and threats that artificial intelligence and its areas, such as machine learning or deep learning, pose to financial market participants. The research methods utilized in the study were used to evaluate the phenomenon on a macroeconomic scale. Methodology. The results of the research were based on the analysis of secondary data, such as source literature – both domestic and foreign, systems analysis of European Union legal acts, as well as the review of reports on the use of AI within the financial market. The paper is theoretical. The result of the research. The development of artificial intelligence in financial markets may provide an opportunity to gain competitive advantage, especially for financial market participants who aptly implement AI-based solutions in its initial phase. However, this entails both benefits and risks, the possible occurrence of which depends on many other factors.

Since the early 2000s, personalized medicine (PM) has been a much-hyped field of healthcare. HIV treatment optimization tools were one of the first successful examples of PM, and have since their development been used to find tailored and optimized treatment for HIV-positive people. In this paper on a case study of the social arena of personalized HIV therapy I show how social worlds worked on both shared and distinct goals within the arena. I highlight the simultaneous centering and marginalization to which people seeking HIV therapy were subjected discursively in the social worlds. I also demonstrate that the further patients were from practitioners' daily work, the more they were reduced to their blood samples, rather than being constructed as complex and human.

Copyright of Yearbook of Swiss Administrative Sciences is the property of Ubiquity Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Manual yield estimation usually requires a lot of work and is expensive. With the help of modern image recognition systems, it is already possible to create yield forecasts to determine area-related yield capacity and fruit size distribution. This makes it possible to apply cultivation measures in a more targeted way and to optimize storage and logistics. Therefore, in this paper, five different commercially available systems were tested for their precision and practicality with different varieties and at different locatins. For this purpose, the data obtained were compared with manually determined data and the deviation was calculated. It was found that there were large differences between the various systems, although some systems already showed sufficient accuracy. Most of the systems, however, had too much deviation and the time required to collect the data was often higher than that required for manual measurement.

Copyright of Deutsches Institut für Wirtschaftsforschung: DIW-Wochenbericht is the property of DIW Berlin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the results obtained from the testing of an algorithm based on artificial intelligence applied to data on cattle breeding, over a period of several years. Following the application of this algorithm can be made predictions regarding the weight gain of cattle according to their age, their type, the input weight and the number of days we propose to keep him fattening. Prediction can help us make decisions about future sales contracts, simply by the fact that we can know a weight that we can achieve for existing cattle after a certain number of days.

There has been extensive work on understanding belief, from a psycho-logical, philosophical and neurobiological perspective. Meanwhile, arti-ficial intelligence has produced compelling developments that can enrich and update the brain-as-a-computer metaphor and has tried to better represent beliefs as cognitive probabilistic processes. In parallel, there has been a surge of research in Complexity Sciences, with applications rang-ing from Medicine to Finance. Some authors have already linked the con-nected nature of belief to the behaviour of complex networks. We would like to expand this approach to understand belief as a complex system with the main functions of providing a model of the world – including the individual and her surroundings – and producing guidelines for action. The complex-system perspective allows us to understand some of the properties of belief systems in a comprehensive manner, which many authors have begun to study in isolation. Notably, this provides a framework to study the impor-tant phenomena of belief formation and change as processes of emergence and adaptation. In this exploratory paper, we propose an outline for this framework for this study.

Apart from traditional deep learning tasks such as pattern recognition, stock price prediction, and machine translation, this method also finds practical application within algorithmic composition. This paper explores the use of a generative model based on unsupervised learning of a musical style from a pre-selected corpus and the subsequent prediction of samples from the estimated distribution. The model uses a Long Short-Term Memory neural network whose training data contains genre-specific melodies in symbolic representation.