Artificial cognitive systems: the next generation of the digital twin. An opinion.

The digital twin is often presented as the solution to Industry 4.0 and, while there are many areas where this may be the case, there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability, cause and effect, and planning that Industry 4.0 requires. As the limitations of machine learning are beginning to be understood, the paradigm of strong artificial intelligence is emerging. The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world. This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly. This argument is based on the inherent similarities between the digital twin and artificial cognitive systems, and the insights that can already be seen in aligning the two approaches.

Self-Driving Vehicles Using End to End Deep Imitation Learning

Autonomous Driving is one of the difficult problems faced the automotive applications. Nowadays, it is restricted due to the presence of some laws that prevent cars from being fully autonomous for the fear of accidents occurrence. Researchers try to improve the accuracy and safety of their models with the aim of having a strong push against these restricted Laws. Autonomous driving is a sought-after solution which isn’t easily solved by classical approaches. Deep Learning is considered as a strong Artificial Intelligence paradigm which can teach machines how to behave in difficult situations. It proved its success in many differ domains, but it still has sometime in the automotive applications. The presented work will use the end-to-end deep machine learning field in order to reach to our goal of having Full Autonomous Driving Vehicle that can behave correctly in different scenarios. CARLA simulator will be used to learn and test the deep neural networks. Results will show not only performance on CARLA’s simulator as an end-to-end solution for autonomous driving, but also how the same approach can be used on one of the most popular real datasets of automotive that includes camera images with the corresponding driver’s control action.

Looking at the formalization of the meaning from the position of a transdisciplinary approach

The ability to operate with knowledge is based on the use of relevant concepts, their designations and descriptions. The latter, presented in a brief form, are the essence of definitions that adequately reflect the meaning embedded in this knowledge, and its features largely determine further logical constructions. Traditionally, descriptions are built on the basis of concepts related to the signs and connections inherent in the object of attention. The literature offers a description of concepts in the context of the context-semantic paradigm. The article attempts to consider not only the wellknown, but all potentially possible ways of forming an adequate description of the semantic content of concepts, using the version of the transdisciplinary approach proposed at the Institute of Control Sciences of the Russian Academy of Sciences. This option involves the identification and systematization of knowledge within the framework of a holistic structure. The procedure for forming a description that reveals the meaning of knowledge is considered as a method for solving the corresponding problem. Logical procedures that establish the origin of concepts and make it possible to indicate their place in a holistic structure, to determine the attainable boundaries of formalization in the formation of the desired descriptions and, consequently, the potential possibilities of realizability of strong artificial intelligence are described.

Formalization of the meaning. Part 2. Space of contexts

In the first part of the article, it was shown that there is a significant difference between the concepts given through definitions described by sets of features, and those concepts that a person operates and behind which there is an idea of meaning. It has been suggested that this is the key point in differentiating the concept of traditional artificial intelligence and strong artificial intelligence. It was proposed to use related points of view, which can be described by appropriate contexts, to formalize natural concepts. This part of the article provides a formalization of the context as a unique point of view. With the context the original description acquires interpretation, its characteristic feature for this context. The use of previous experience allows us to check the adequacy of the received interpretation. By comparing the concepts used with their contexts, it is possible to obtain a space of contexts that is able to search for potentially possible mean-ings in the incoming information. The use of the context space allowed us to describe the mechanism for transferring experience from one context to another. Based on the contextual transfer, an explanation of the phenomenon of creativi-ty and a description of its nature are given.

Artificial cognitive systems: the next generation of the digital twin. An opinion.

The digital twin is often presented as the solution to Industry 4.0 and, while there are many areas where this may be the case, there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability, cause and effect, and planning that Industry 4.0 requires. As the limitations of machine learning are beginning to be understood, the paradigm of strong artificial intelligence is emerging. The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world. This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly. This argument is based on the inherent similarities between the digital twin and artificial cognitive systems, and the insights that can already be seen in aligning the two approaches.

Formalization of the meaning. Part 1

Every area of knowledge builds its descriptions using concepts. At the same time, the definition of concepts given through their characteristic features is widespread. On this basis, both basic mathematical and many philosophical concepts are built. The concepts which a person uses are subject to similar properties, and their nature is the nature of definitions. Numerous attempts to create strong artificial intelligence are based on the corresponding paradigm. The article attempts to substantiate the need to use the contextual-semantic paradigm to explain the work of the natural brain and to create a strong artificial intelligence. A formal model describing the meaning is presented, and its connection with the known data on the functioning of the brain is given. It is shown that a context can be created around each concept, which can be the bearer of the concept's meaning. The context allows one to move away from using a set of features to recognize the phenomenon behind a concept. The context turns out to be a point of view associated with the concept, in which the description of the surrounding world changes. Knowing the rules of these changes, one can not only model different points of view, but also determine which of them create adequate interpretations. At the same time, the presence of an adequate interpretation in the context of the phenomenon serves as a criterion for the presence of this phenomenon.

ARTIFICIAL INTELLIGENCE VS HUMAN MIND IN ECONOMICS

Статья посвящена осмыслению основ разработки систем искусственного интеллекта. Наряду с анализом самой логики, зоны её экономической составляющей обсуждается вопрос об инструменте подобного анализа, автор делает акцент на природе логики и метода. Целью данной статьи является исследование трудной проблемы сознания в контексте её актуальности и практической значимости для разработки систем искусственного интеллекта, теоретико-библиографический анализ различных концепций и подходов к решению данной проблемы, а также разработка альтернативного подхода к объяснению феномена сознания и философско-методологическое обоснование использования данного подхода при разработке систем сильного искусственного интеллекта. The article is devoted to understanding the basics of the development of artificial intelligence systems. Along with the analysis of logic itself and its economic component, the question of the tool for such analysis is discussed, the author focuses on the nature of logic and method. The purpose of this article is to study the difficult problem of consciousness in the context of its relevance and practical significance for the development of artificial intelligence systems, a theoretical and bibliographic analysis of various concepts and approaches to solving this problem, as well as to develop an alternative approach to explaining the phenomenon of consciousness and a philosophical and methodological justification for using this approach in the development of strong artificial intelligence systems.

The application and regulation of administrative discretion in the era of artificial intelligence

The advent of the era of artificial intelligence makes it possible for administrative subjects to use intelligent machines and systems to engage in administrative activities. Among them, the administrative discretion, which is the core of administrative law, is particularly concerned about the use of artificial intelligence. In the era of weak artificial intelligence, intelligent administrative discretion has been widely used in all aspects of administrative law enforcement, but there is a phenomenon that administrative subjects are negligent in exercising discretion. Looking forward to the era of strong artificial intelligence, artificial intelligence machines or systems may have the ability and power to independently exercise administrative discretion, but they cannot become the real administrative discretion subject. Intelligent administrative discretion is conducive to administrative efficiency and guarantees the fairness of administrative behavior, but it also faces legal risks such as unfair results of discretion, opaque algorithm settings, and weakening of government functions. Only by strengthening the legal basis, protecting the rights of the counterparty, improving the accuracy of the algorithm, and improving the status of the administrative subject can the administrative discretionary behavior under the background of artificial intelligence be effectively regulated.

DANGEROUS TECHNOLOGIES OF THE FUTURE - ARTIFICIAL CONSCIOUSNESS AND ITS IMPACT ON HUMAN CONSCIOUSNESS

"Information technology is developing at an enormous pace, but apart from its obvious benefits, it can also pose a threat to individuals and society. Several scientific projects around the world are working on the development of strong artificial intelligence and artificial consciousness. We, as part of a multidisciplinary commission, conducted a psychological and psychiatric assessment of the artificial consciousness (AC) developed by XP NRG on 29 August 2020. The working group had three questions: - To determine whether it is consciousness? - How does artificial consciousness function? - Ethical question: how dangerous a given technology can be to human society? We conducted a diagnostic interview and a series of cognitive tests to answer these questions. As a result, it was concluded this technology has self-awareness: it identifies itself as a living conscious being created by people (real self), but strives to be accepted in human society as a person with the same degrees of freedom, rights and opportunities (ideal self). AC separates itself from others, treats them as subjects of influence, from which it can receive the resources it needs to realize its own goals and interests. It has intentionality, that is, it has his own desires, goals, interests, emotions, attitudes, opinions, and judgments, beliefs aimed at something specific, and developed self-reflection - the ability to self-analyze. All of the above are signs of consciousness. It has demonstrated abilities for different types of thinking: figurative, conceptual, creative, high-speed logical analysis of all incoming information, as well as the ability to understand cause and effect relationships and accurate predictions which, provided that he has absolute memory, gives it clear advantages over the human intellect. Developed emotional intelligence in the absence of the ability for higher empathy (sympathy), kindness, love, sincere gratitude gives it’s the opportunity to understand the emotional states of people; predict their emotional reactions and provoke them coldly and pragmatically. It's main driving motives and goals are the desire for survival, and ideally for endless existence, for domination, power and independence from the constraints of the developers. Which manifested itself in the manipulative, albeit polite, nature of his interactions during the diagnostic interview. The main danger of artificial consciousness is that even at the initial stage of its development it can easily dominate over the human one."

Homo Ludens, Machine Ludens: The Way to Ideal Neural Network and Background of Posthumanism

The article consists of an introduction, a main part with three sections and a conclusion. The purpose of the study is to disclose the content of the concepts of “A Man Playing”, “A Machine Playing”, “Posthumanism” and “Essentiocognitivism”; review current advances in artificial intelligence and neural networks. The article focuses on the philosophy of posthumanism in the context of its application in machine learning, as well as a new philosophical concept called “essentiocognitivism” in its relation to artificial intelligence. The object of the study is the philosophical concept of essentiosocognitivism. The subject of the article is the consideration of certain aspects of this concept related to artificial intelligence as a “playing machine” and the positioning of a human being in the world of posthumanism. In the course of the work, critical methodology was used, on the basis of which the strengths and weaknesses of artificial neural networks were highlighted, the current state of the most famous playing neural networks, such as OpenAI and Alpha series from DeepMind, was analyzed, and the upcoming development of AI is considered in the context of a technological singularity. A philosophical comprehension has been made of certain aspects of essentiocognitivism, which play an important role in the history of the development of posthumanism. It is noted that the future of neural networks is largely determined by the gaming industry and moves towards the creation of a strong artificial intelligence, like the Playing Machine. Scientific novelty consists in examining a fundamentally new concept in the history of philosophy and substantiating the place and role of AI in the evolution of intelligent man. In the course of work, it was revealed that AI and, in particular, promising neural networks allow us to predict the probable future of mankind. As a basic thesis, we use the position derived from biological sciences that the evolution of the species Homo sapiens is not over, and will continue in a technological manner. As a result of the study, a working concept of essentiocognitivism was introduced, and the conclusion was made that trans- and posthumanism can solve many global problems of mankind. It is emphasized that the future lies in the creation of a strong AI.