Search

The advent of artificial intelligence (AI) has expanded the scope and meaning of digital labor, revealing certain positive factors that could potentially lead to labor liberation and the comprehensive development of human freedom. However, at its core, the positive aspects of digital labor in the AI era are ultimately geared towards the inherent nature of capital self-expansion. It still relies on the appropriation of human creativity as a prerequisite and reinforces alienated labor by separating human intelligence from the individual. In view of Karl Marx, the alienation of labor stems from the capitalist application of the machinery, while on the contrary the application of machinery is separated from their capitalist use within the machine system. Therefore, in the AI era, because the digital labor contributes to the comprehensive development of human freedom by reducing necessary labor time and transforming human-machine relations, it is essential to harness capital and establish ethical legislation for AI technology. [ABSTRACT FROM AUTHOR]

Computing in memory (CIM) breaks the conventional von Neumann bottleneck through in situ processing. Monolithic integration of digital and analog CIM hardware, ensuring both high precision and energy efficiency, provides a sustainable paradigm for increasingly sophisticated artificial intelligence (AI) applications but remains challenging. Here, we propose a complementary metal-oxide semiconductor-compatible ferroelectric hybrid CIM platform that consists of Boolean logic and triggers for digital processing and multistage cell arrays for analog computation. The basic ferroelectric-gated units are assembled with solution-processable two-dimensional (2D) molybdenum disulfide atomic-thin channels at a wafer-scale yield of 96.36%, delivering high on/off ratios (>107), high endurance (>1012), long retention time (>10 years), and ultralow cycle-to-cycle/device-to-device variations (~0.3%/~0.5%). Last, we customize a highly compact 2D hybrid CIM system for dynamic tracking, achieving a high accuracy of 99.8% and a 263-fold improvement in power efficiency compared to graphics processing units. These results demonstrate the potential of 2D fully ferroelectric-gated hybrid hardware for developing versatile CIM blocks for AI tasks. [ABSTRACT FROM AUTHOR]

Due to its powerful brain‐like parallel computing and efficient data processing capabilities, memristors are considered to be the core components for building the next generation of artificial intelligence systems. In this study, the CeOx/WOy heterojunction is employed as the functional layer, and various metal materials are utilized as the top electrode to fabricate the memristor. The results indicate that the memristive performance of the Ag/CeOx/WOy/ITO device can be improved by using Ag as the top electrode. By studying the conductivity mechanism of the device, a conductivity model is established that regulates oxygen vacancies and Ag conductive filaments. Furthermore, using the as‐prepared memristor, it is constructed four basic digital logic circuits: OR, AND, XOR, and XNOR, as well as a half adder and a full adder that can be used for digital arithmetic operations. Specifically, an odd/even checker is developed based on XOR and XNOR logic circuits to verify the correctness of data transmission. Finally, it is also designed and implemented a cryptographic array based on a memristor, which can be applied to encrypt and decrypt a series of numbers and images. Therefore, this work extends the application of memristor toward digital circuits, information transmission, data processing and image security encryption. [ABSTRACT FROM AUTHOR]

This article discusses the intersection of technology and the law, specifically focusing on the transformation of legal imagination in the tech era. The authors argue that there is a need to critically examine the historical and future implications of this transformation. The article explores various topics within this context, including the impact of digitalization, datafication, and AI on the law, the role of technology in shaping legal decision-making and enforcement mechanisms, and the challenges and possibilities of legal imagination in the face of new technologies. The authors also highlight the importance of considering diverse perspectives and the cultural and societal implications of tech-induced legal change. [Extracted from the article]

Since the early days of artificial intelligence (AI), many logics have been explored as tools for knowledge representation and reasoning. In the spirit of the Crossley Festscrift and recognizing John Crossley's diverse interests and his legacy in both mathematical logic and computer science, I discuss examples from my own research that sit in the overlap of logic and AI, with a focus on supporting human–AI interactions. [ABSTRACT FROM AUTHOR]

The article presents an interview with Dr. María José Frápolli, a philosopher and professor of logic and philosophy of science. Dr. Frápolli reflects on her career and her interest in understanding what kind of animal we are and how different philosophical positions help us understand ourselves. She also talks about her commitment to the cause of female philosophers and how the ethical evolution of feminisms is influencing the development of philosophy. The article highlights the importance of Dr. Frápolli's academic production in the fields of logic and semantics research. In this interview, Dr. María José Frápolli discusses the distinction between logic and calculations, stating that calculations are instruments for representing and evaluating inferences. She points out that classical logic calculations derive from Frege's proposal in Conceptography and are designed for the foundation of arithmetic. Additionally, she mentions that non-classical logics arise due to the need to represent inferences in different areas of discourse and that each proposal of non-classical logic can vary according to its purposes of representation and evaluation. Finally, she comments that it is possible to classify existing logics in different ways, but she does not see scientific or philosophical advantages in doing so. She also highlights Susan Haack's distinction between extensions and divergent logics, considering it intuitive and showing the complexity of inferential relationships between propositions. In this interview, Dr. María José Frápolli talks about the changes in research objectives in logic from the early 20th century to the present. She mentions that there has been a greater interest in representing semantic features of natural language and pragmatic aspects. She also highlights the development of computer theory and artificial intelligence. Regarding logical pluralism, Dr. Frápolli mentions that she would not bet on any particular calculation and that each one has its own presuppositions and purposes. Additionally, she points out that logic has not been very useful as an applied discipline in other scientific areas. The text presents an interview with Dr. María José Frápolli about the application of logic in different disciplines. It is mentioned that fuzzy logics and computer theory are exceptions in their application. Dr. Frápolli mentions that logic has a promising field of application in proof theory, computing, and artificial intelligence. The general usefulness of logic in the current world is also discussed, and its role in the development of critical thinking and reasoning is highlighted. As for branches of logic with promising applications, those related to programming languages and artificial intelligence are mentioned as the most prominent. [Extracted from the article]

Artificial intelligence (AI) possesses high adaptability and potential to replace human mental labor. However, only environments with high-performance computing resources and large power supplies can handle AI processing. Current computing technology is based on digital logic devices, leading to the inevitability of endless fetching of data among processors and memories. Moreover, acceleration of AI has been mainly studied at the software level, e.g., pruning of neural networks, which is insufficient for overcoming processing environment restrictions. Meanwhile, in-memory computing by physically composed neural networks is an emerging field. Resistive switching memory (RRAM) is a promising option, which is yet to be implemented because of the stochastic nature of the switching process. In this work, the temporal reliability of tantalum oxide-based RRAM was dramatically enhanced (∼1%) by the insertion of a rough titanium oxide thin film. The enhanced devices exhibited a classification accuracy of ∼88%, showing superior performance and application potential for neuromorphic computing. [ABSTRACT FROM AUTHOR]

Introduction: The platform economy has invaded social relations in every way. Products of the information revolution, artificial intelligence and big data, the platforms constitute a sign of the times that crosses and deepens the set of pre-existing mercantile relations while commodifying a series of activities that, until their arrival, were outside to data extractive logic. The consequences of this irruption for the world of work are multiple and profound. Objectives: Here we propose to analyze the control practices and working conditions at UBER, the company that constitutes a paradigm of the new work management logics through digital platforms. Methodology: The study is qualitative in nature, based on ten in-depth interviews with UBER drivers during the years 2019 and 2020, in which, among other dimensions, working conditions, control mechanisms and meanings of work were investigated. Likewise, periodic monitoring of two driver and passenger forums was carried out. Results: Throughout the writing, a multiplicity of daily practices developed by the Uber company to influence the behavior and control the activity of drivers is observed. The platform's capacity to algorithmically manage work in a massive and personalized way is verified, with significant effects on working conditions. Conclusions: The study concludes that, far from the situation of autonomy proposed from business narratives, uberized work supposes significant degrees of dependency, control and exploitation of the workforce. Likewise, it is observed that the irruption of the platforms supposes a new stage in the deepening and extension of the relative vulnerability of work. [ABSTRACT FROM AUTHOR]

The article substantiates the hypothesis that there is no alternative to digital transformation of business, public administration, and society as a whole in the current composition of scientific and technological trends in global development. The article systematically identifies digital technologies based on big data, grid computing, blockchain and actually implemented in global business, such as the industrial Internet, robotics, digital marketing, fintech, govtech, e-medicine and education, etc. It is emphasised that they are the key drivers of the digital economy as a new phenomenon and a new reality. The author summarises the conceptual and categorical apparatus and shows the archetypes of the digital economy. Its status is illustrated in the format of indicators of influential global indices. The article states the obvious positive aspects of digitalisation of the economy - accessibility, transparency and efficiency of resource use, high productivity and cheaper services, fast access to markets, communication mobility, energy efficiency and environmental friendliness - and shows its possible negative aspects, such as cybercrime, electricity shocks, unemployment, insecurity of personal information, discrediting traditional cultural and behavioural values. A SWOT analysis of the digitalisation of the Ukrainian economy according to the Global Digital Competitiveness and Network Readiness indices is carried out and the ways and priority tasks of its intensification in the European integration direction of development are outlined - 4G mobile coverage, availability of clean energy, neutralisation of high investment risks, proper legal regulation of intellectual property and ICT activities. The key role of e-governance strategies and practices in the process of digital transformation of national economies is substantiated on the basis of a comparative cross-country analysis. The author's own logic of digital economy transformation is presented, based on promising scientific and technological trends generated by nano-, bio-, neuro-, quantum- and artificial intelligence. The author substantiates the objective conditionality of the formation of a smart economy, primarily in the format of smart enterprises, cities and communities. [ABSTRACT FROM AUTHOR]

[Purpose] The purpose of this study is to determine ways to introduce artificial intelligence into the Ukrainian justice system. [Methodology/Approach/Design] The methodological basis of the study consists of theoretical and specialised legal methods: philosophical approaches, general and special methods of modern legal science, which are to interpret the law, and also general scientific styles. [Findings] During the study, the features of the use of artificial intelligence in the justice system were established and an analysis of international experience in the use of artificial intelligence in the justice system was conducted, which allowed identifying positive and negative aspects in the practice of other countries. In addition, problems that may hinder the development of artificial intelligence in the justice system of Ukraine and positive trends in the introduction of this innovative communication technology were identified. Based on the identified disadvantages and advantages of using artificial intelligence in justice, it was determined which systems should be implemented in the Ukrainian justice system, in particular the 'judge's companion' system. However, it is evident that at the moment artificial intelligence cannot completely replace people. [ABSTRACT FROM AUTHOR]

Artificial synapses have attracted extensive attention due to their capacity to circumvent the inherent restrictions of Von Neumann computing architecture. Although electrolyte‐gated synaptic transistors (EGSTs) have been enabled to emulate the essential synaptic plasticity, the corresponding neurological applications have been restricted by the lack of inhibitory synaptic response and the subsequent low asymmetric non‐linearity factor. Here, Mg‐doped SnO2 (Mg:SnO2) EGSTs via a low‐cost and facile solution method are fabricated. With both excitatory and inhibitory response modes, the improved MgSnO EGSTs display variable synaptic plasticity, with featured characteristics such as excitatory post‐synaptic current (EPSC), inhibitory post‐synaptic current (IPSC), paired pulse facilitation (PPF), paired pulse depression (PPD), spiking rate dependent plasticity (SRDP), and spike timing dependent plasticity (STDP). For the University of California at Irvine image, a simulated artificial neural network built on MgSnO EGSTs may achieve a learning accuracy of 92.3%. In addition, digital logic processing, Pavlovian dog's experiment have all been realized by the newly designed MgSnO EGSTs. These results highlight the potential of the MgSnO EGSTs for next‐generation artificial intelligence systems. [ABSTRACT FROM AUTHOR]

As an emerging two-terminal device, memristors have attracted extensive interest due to their integration of memory and computing, which can drastically boost the progress of high-density storage and artificial intelligence. Recently, organometal trihalide perovskites (OTPs) were reported to be promising active materials for photoelectronic applications. In this manuscript, a CsFAMAPbIBr-based memristor with a structure of W/Cs0.05(FAxMA1−x)0.95PbBryI3−y/ITO is presented. By applying sweeping voltage with different amplitudes or scanning speed, the memory characteristic of the device can be tuned to realize the conversion between analog and digital. Furthermore, we elaborate the conversion mechanism in detail mainly by space-charge-limited conduction. This work paves a way for analyzing the influence of external applied voltage on memristor characteristics and could be beneficial to the potential application in digital logic application and neuromorphological analysis. [ABSTRACT FROM AUTHOR]

The present work is aimed at using the artificial intelligence (AI) algorithm to study the promotion and publicity of ice and snow tourism (IST). Firstly, the urgent needs of IST external publicity are analyzed based on digital technology. Besides, the dynamic vision sensor technology is used to collect data in the distributed Internet of Things structure of the IST publicity system. Then, the AlexNet algorithm is combined with the digital logic method. The research assumption is that the complete IST image based on AI can be formed according to the AlexNet algorithm. The improved AlexNet algorithm and Chi-square test implement the IST poster emotion recognition and IST publicity model. Then, the intelligent customer service of the IST publicity platform is studied. The results demonstrate that after 120 iterations, the accuracy of the sports-oriented publicity method based on AlexNet can reach about 75%. In addition, the accuracy of the recommended IST publicity algorithm based on AlexNet is close to 90% after 80 iterations. Therefore, the model's accuracy is improved by at least 9.6% compared with the traditional method. The research has practical application value for the digital and intelligent development of the IST industry. [ABSTRACT FROM AUTHOR]

In the era of digital capitalism, machines and technology have gradually become the main body that dominates workers. Information technology is actually the digital embodiment of mass machine production. It is with the help of ICT and digital technology that digital capitalism realizes the digital transformation of the way capitalism exists and the proliferation of digital capital. The purpose of this paper is to study the generative logic of digital capitalism based on artificial intelligence technology. Compare the production, circulation, consumption of traditional commodities, and the production of digital capital, explore the nature of digital capitalism and the differentiation of digital capitalism in the era of artificial intelligence, analyze the impact of artificial intelligence on labor polarization, and the results show the high-skilled labor force in the eastern region. The ratio to the medium-skilled labor force is 0.086. Take the M enterprise in capitalism as an example, and study the application of artificial intelligence to the energy and power industry to provide value to customers through new products. The new changes in contemporary artificial intelligence capitalism solve the problems in the operation of the original business model, benefiting both customers and enterprises. [ABSTRACT FROM AUTHOR]

In the modern Block-chain and Artificial Intelligence era, energy efficiency has become one of the most important design concerns. Approximate computing is a new and an evolving field promising to provide energy-accuracy trade-off. Several applications are tolerant to small degradation in results, and hence tasks like image and video processing are candidates to benefit from Approximate Computing. In this paper, we propose a new design approach for designing approximate adders and further optimize the accuracy and cost metrics. Our approach is based on minimizing the errors while cascading more than one 1-bit adder. We insert | error | = 1 on specific locations to achieve a reasonable circuit minimization and reduce the error × count gate cost. We compare our design with exact adder and relevant state-of-the-art approximate adders. Through analysis and simulations, we show that our approach provides higher accuracy and far better performance compared with other designs. The proposed double bit approximate adder provides more than 25% savings in gate count compared with the exact adder, has a mean absolute error of 0.25 which is lowest among all the reference approximate adders and reduces the power-delay product by more than 60% compared to the exact adder. When employed for image filtering, the proposed design provides a PSNR avg of 96%, a SNR avg of 95% and a SSIM avg of 91% relative to the actual results, while the second best approximate adder only achieves 64%, 54% and 71% of these image quality metrics, respectively. [ABSTRACT FROM AUTHOR]

The importance of intuitionistic temporal logics in Computer Science and Artificial Intelligence has become increasingly clear in the last few years. From the proof-theory point of view, intuitionistic temporal logics have made it possible to extend functional programming languages with new features via type theory, while from the semantics perspective, several logics for reasoning about dynamical systems and several semantics for logic programming have their roots in this framework. We consider several axiomatic systems for intuitionistic linear temporal logic and show that each of these systems is sound for a class of structures based either on Kripke frames or on dynamic topological systems. We provide two distinct interpretations of "henceforth", both of which are natural intuitionistic variants of the classical one. We completely establish the order relation between the semantically defined logics based on both interpretations of "henceforth" and, using our soundness results, show that the axiomatically defined logics enjoy the same order relations. [ABSTRACT FROM AUTHOR]

Traditionally, insurers have gathered underwriting informationfrom insurance consumers using policy application forms,credit checks/Dun & Bradstreet reports, and publicly availableinformation from government or industry sources. Theattractiveness of AI for insurers is clear, as it takes much of theguesswork -- and indeed risk -- out of the insurance process,combined with blockchain (above) and the IoT (below)capabilities. Given that insurers have argued and could again argue thatthe way in which they collect this data constitutes a tradesecret, it could be difficult for insurance consumers to forceinsurers to disclose exactly how they're getting underwritingand rating information.[10] It's possible that the Fair CreditReporting Act might enable consumers denied insurancesome right to know the basis for the denial and possibly alitigation recourse. Blockchainenables insurers to potentially gather and utilize a muchbroader array of information from sources of which consumers are unaware or that they would not necessarily anticipateas being a resource for underwriters. [Extracted from the article]

Although soft devices (grippers, actuators, and elementary robots) are rapidly becoming an integral part of the broad field of robotics, autonomy for completely soft devices has only begun to be developed. Adaptation of conventional systems of control to soft devices requires hard valves and electronic controls. This paper describes completely soft pneumatic digital logic gates having a physical scale appropriate for usewith current (macroscopic) soft actuators. Each digital logic gate utilizes a single bistable valve--the pneumatic equivalent of a Schmitt trigger--which relies on the snap-through instability of a hemispherical membrane to kink internal tubes and operates with binary high/low input and output pressures. Soft, pneumatic NOT, AND, and OR digital logic gates--which generate known pneumatic outputs as a function of one, or multiple, pneumatic inputs--allow fabrication of digital logic circuits for a set-reset latch, two-bit shift register, leading-edge detector, digital-to-analog converter (DAC), and toggle switch. The DAC and toggle switch, in turn, can control and power a soft actuator (demonstrated using a pneu-net gripper). These macroscale soft digital logic gates are scalable to high volumes of airflow, do not consume power at steady state, and can be reconfigured to achieve multiple functionalities from a single design (including configurations that receive inputs from the environment and from human users). This work represents a step toward a strategy to develop autonomous control--one not involving an electronic interface or hard components--for soft devices. [ABSTRACT FROM AUTHOR]

The question at the heart of this essay begins with a curious mid-twentieth-century co-occurrence in the Anglo-American world: on the one hand, of the invention and transformative spread of digital computing; on the other hand, the return from philosophical exile of "ontology" and its subsequent pluralization. What makes this co-occurrence interesting is, first, the machine's requirement of a "model"—and so an ontology—of the domain to be affected, and second, the indeterminate nature of all digital models. Furthermore, as improvements in the technology have made the machine an ever more fit instrument of that "wily intelligence" (mẽtis) celebrated by Marcel Detienne and Jean-Pierre Vernant (1974), the laborious construction of models has become the agile practice of modeling—and so brought ever greater emphasis to local, experimental, shifting ontologies. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses the historical use of computer logic programming for teaching History, emphasizing how Artificial Intelligence (AI) tools are now being harnessed to encourage critical thinking in students and transform the way History is taught.

Reducing power consumption in nowadays computer technologies represents an increasingly difficult challenge. Conventional computing architectures suffer from the so-called von Neumann bottleneck (VNB), which consists in the continuous need to exchange data and instructions between the memory and the processing unit, leading to significant and apparently unavoidable power consumption. Even the hardware typically employed to run Artificial Intelligence (AI) algorithms, such as Deep Neural Networks (DNN), suffers from this limitation. A change of paradigm is so needed to comply with the ever-increasing demand for ultra-low power, autonomous, and intelligent systems. From this perspective, emerging memristive non-volatile memories are considered a good candidate to lead this technological transition toward the next-generation hardware platforms, enabling the possibility to store and process information in the same place, therefore bypassing the VNB. To evaluate the state of current public-available devices, in this work commercial-grade packaged Self Directed Channel memristors are thoroughly studied to evaluate their performance in the framework of in-memory computing. Specifically, the operating conditions allowing both analog update of the synaptic weight and stable binary switching are identified, along with the associated issues. To this purpose, a dedicated yet prototypical system based on an FPGA control platform is designed and realized. Then, it is exploited to fully characterize the performance in terms of power consumption of an innovative Smart IMPLY (SIMPLY) Logic-in-Memory (LiM) computing framework that allows reliable in-memory computation of classical Boolean operations. The projection of these results to the nanoseconds regime leads to an estimation of the real potential of this computing paradigm. Although not investigated in this work, the presented platform can also be exploited to test memristor-based SNN and Binarized DNNs (i.e., BNN), that can be combined with LiM to provide the heterogeneous flexible architecture envisioned as the long-term goal for ubiquitous and pervasive AI. [Display omitted] • Smart Imply (SIMPLY) facilitates memristor-based digital Logic in Memory (LiM). • SIMPLY is possible even with commercial-available memristors. • FPGA-based platform is developed to evaluate SIMPLY operation's energy consumption. • Results show great advantages with respect to CMOS counterpart and other reports. [ABSTRACT FROM AUTHOR]

This article has been retracted by Hindawi following an investigation undertaken by the publisher [[1]]. Wiley and Hindawi regrets that the usual quality checks did not identify these issues before publication and have since put additional measures in place to safeguard research integrity. We wish to credit our own Research Integrity and Research Publishing teams and anonymous and named external researchers and research integrity experts for contributing to this investigation. [Extracted from the article]

Preferences play a crucial role in the theory of rationality, and therefore also to computational social choice and artificial intelligence. In formal models it is usually assumed that preferences are primitive objects, and little concern is devoted to the question of how they are formed or where they come from. Recent work in rational choice theory challenges this assumption, however, and aims to give more internal structure to the notion of a preference. The focus so far has been on modeling faculties of individual agents, such as their mood, mindset, and motivating reasons. In this paper we contribute to this development by developing a modal logic for reasoning about preferences that depend on a set of motivationally salient properties. The main result is a translation showing how reasoning in this logic can be captured by reasoning in a standard modal logic (KT with universal modality). It follows that reasoning systems and algorithms developed for modal logic (with universal modality) can be employed for reasoning about reason-based preferences. We then discuss how the approach can be generalised to the multi-agent case, and allows us to reason about agents who disagree because they are motivated by different factors, and who might be able to reach consensus simply by changing their perspective. [ABSTRACT FROM AUTHOR]

During the centennial year of his birth Alan Turing (1912-1954) has been widely celebrated as having laid the foundations for Computer Science, Automated Decryption, Systems Biology and the Turing Test. In this paper we investigate Turing's motivations and expectations for the development of Machine Intelligence, as expressed in his 1950 article in Mind. We show that many of the trends and developments within AI over the last 50 years were foreseen in this foundational paper. In particular, Turing not only describes the use of Computational Logic but also the necessity for the development of Machine Learning in order to achieve human-level AI within a 50 year time-frame. His description of the Child Machine (a machine which learns like an infant) dominates the closing section of the paper, in which he provides suggestions for how AI might be achieved. Turing discusses three alternative suggestions which can be characterised as: (1) AI by programming, (2) AI by ab initio machine learning and (3) AI using logic, probabilities, learning and background knowledge. He argues that there are inevitable limitations in the first two approaches and recommends the third as the most promising. We compare Turing's three alternatives to developments within AI, and conclude with a discussion of some of the unresolved challenges he posed within the paper. [ABSTRACT FROM AUTHOR]

In the first book review, “Programming from the Bottom Up,”, Norman Chonacky reviews an introductory textbook that considers fundamental computer operations as well as the methods and practices needed to create, use, or manage programs intended for the computational sciences and engineering. In the second book review, “Can Artificial Intelligence Improve Human Reasoning?”' George F. Luger reviews a book dealing with how the rational human mind might be understood and enhanced through computer-based representations and algorithms. [ABSTRACT FROM AUTHOR]