In this paper, we propose some transfor mations based on the centroid points between single valued neutrosophic numbers. We introduce these trans formations according to truth, indeterminacy and falsity value of single valued neutrosophic numbers. We propose a new similarity measure based on falsity value between single valued neutrosophic sets. Then we prove some properties on new similarity measure based on falsity value between falsity value between single valued neutrosophic sets. Furthermore, we propose similarity measure based on falsity value between (...) single valued neutrosophic sets based on the centroid points of transformed single valued neutrosophic numbers. We also apply the proposed similarity measure between single valued neutrosophic sets to deal with pattern recognition problems. (shrink)

What kinds of norms constrain mechanistic discovery and explanation? In the mechanistic literature, the norms for good explanations are directly derived from answers to the metaphysical question of what explanations are. Prominent mechanistic accounts thus emphasize either ontic or epistemic norms. Still, mechanistic philosophers on both sides agree that there is no sharp distinction between the processes of discovery and explanation. Thus, it seems reasonable to expect that ontic and epistemic accounts of explanation will be accompanied by ontic and epistemic (...) accounts of discovery, respectively. As we will show here, however, recent discovery accounts implicitly rely on both ontic and epistemic norms to characterize the discovery process. In this paper, we develop an account that makes explicit that, and how, ontic and epistemic norms work together throughout the discovery process. By describing mechanism discovery as a process of pattern recognition we demonstrate that scientists have to develop epistemic activities to distinguish a pattern from its background. Furthermore, they have to determine which epistemic activities successfully describe how the pattern is implemented by identifying the pattern’s components. Our approach reveals that ontic and epistemic norms are equally important in mechanism discovery. (shrink)

In this paper, we examine how the availability of massive quantities of data i.e., the “Big Data” phenomenon, contributes to the creation, spread, and harms of online misinformation. Specifically, we argue that a factor in the problem of online misinformation is the evolved human instinct to recognize patterns. While the pattern-recognition instinct is a crucial evolutionary adaptation, we argue that in the age of Big Data, these capacities have, unfortunately, rendered us vulnerable. Given the ways in which online (...) media outlets profit from the spread of misinformation by preying on this pattern-finding instinct, we conceptualize the problem that we identify as a morally objectionable form of “epistemic exploitation.” As we argue, the consumer of digital misinformation is often exploited by having her pattern-recognition instinct used against her. This exploitation is morally objectionable because it deprives her of an epistemic good to which she has a right. This epistemic good is the integrity of the pattern-recognition instinct itself which, we argue, is a capacity that allows us to participate in uniquely human goods. While our primary goal is to bring attention to this form of epistemic exploitation, we conclude by briefly evaluating some general solutions to the growing problem of online misinformation. (shrink)

Facial recognition is a computer vision task that involves identifying or verifying individuals based on their facial features. It has widespread applications in security, authentication, and human-computer interaction. Supervised learning techniques have become the foundation for facial recognition systems, as they enable the model to learn from labeled data to recognize patterns and make predictions. This paper explores the use of supervised learning algorithms, such as Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and k-Nearest Neighbors (k-NN), for (...) facial recognition tasks. We will demonstrate how these algorithms can be used to accurately identify individuals by learning from training datasets with labeled facial images. (shrink)

Mutually adaptive interaction involves the robot as a partner as opposed to a tool, and requires that the robot is susceptible to similar environmental cues and behavior patterns as humans are. Recognition, or the acknowledgement of the other as individual, is fundamental to mutually adaptive interaction between humans. We discuss what recognition involves and its behavioral manifestations, and describe the benefits of implementing it in HRI.

The sixth IPCC report states that a proper conception of climate justice that can address the complexity of the phenomenon of anthropogenic climate change as a whole requires considering not only one but rather three dimensions of justice today: redistributive, procedural, and recognition dimensions. In this article, my focus is on exploring the latter dimension, drawing special attention to climate policies addressing cultural-identity issues. In the first section, I illustrate how climate policies can be connected to discriminatory practices against (...) minority cultures and their identities. To do so, I take the struggles of Black movements against environmental racism and the struggles of Indigenous peoples against a colonialist cultural heritage as case studies. In the second section, I look into the most advanced normative model to address the dimension of recognition, its advantages, and how it addresses the so-called ‘institutionalization of cultural patterns’ in climate policies: the Nancy Fraser model. Finally, in the third section, I investigate an aspect that remains open. It concerns the matter of how to use institutional authority to ‘deinstitutionalize’ non-ecological cultural patterns, while respecting pluralism and avoiding falling into the risks of institutional paternalism. (shrink)

Hatred of America expressed in the September 11th attack is more than matched by the hatred by Americans for Islamists expressed in the war on Afghanistan, the War against Terror and the threatened wars against the “Axis of Evil”. It is argued here that there is a pattern of self-reinforcing hatred operating in the world set in motion by the actions of the United States, particularly by George Bush Snr. and embraced and used by George Bush Jr. to reinforce (...) and further develop this pattern. To oppose this it is necessary to understand how hatred is generated, how this system operates and how Bush is exploiting it, and then to provide an alternative. It is argued this requires a new story of civilization as the quest for justice understood as true recognition to oppose to the myths based on hatred promulgated by Bush. In terms of this story, the extreme economic, social, political and military policies of Bush and the myths used to justify them should be recognized for what they are, the challenge of barbarism to civilization. (shrink)

Pattern recognition is represented as the limit, to which an infinite Turing process converges. A Turing machine, in which the bits are substituted with qubits, is introduced. That quantum Turing machine can recognize two complementary patterns in any data. That ability of universal pattern recognition is interpreted as an intellect featuring any quantum computer. The property is valid only within a quantum computer: To utilize it, the observer should be sited inside it. Being outside it, the (...) observer would obtain quite different result depending on the degree of the entanglement of the quantum computer and observer. All extraordinary properties of a quantum computer are due to involving a converging infinite computational process contenting necessarily both a continuous advancing calculation and a leap to the limit. Three types of quantum computation can be distinguished according to whether the series is a finite one, an infinite rational or irrational number. (shrink)

Journal bearings play an important role on many rotating machines placed on industrial environments, especially in steam turbines of thermoelectric power plants. Babbitt damage (BD) and excessive clearance (C) are usual faults of steam turbine journal bearings. This paper is focused on achieving an effective identification of these faults through an intelligent recognition approach. The work was carried out through the processing of real data obtained from an industrial environment. In this work, a feature selection procedure was applied in (...) order to choose the features more suitable to identify the faults. This feature selection procedure was performed through the computation of typical testors, which allows working with both quantitative and qualitative features. The classification tasks were carried out by using Nearest Neighbors, Voting Algorithm, Naïve Associative Classifier and Assisted Classification for Imbalance Data techniques. Several performance measures were computed and used in order to assess the classification effectiveness. The achieved results (e.g., six performance measures were above 0.998) showed the convenience of applying pattern recognition techniques to the automatic identification of BD and C. (shrink)

Computer vision, or image recognition, analyses and interprets visual data in real-world scenarios like images and videos. AI and ML research focusses on object, scene, action, and feature identification because of its usefulness in image processing. Neural networks and deep learning have improved image recognition systems significantly in recent years. Early image recognition used template matching to identify objects. A photo is compared to a stored template using similarity measures like correlation to get the best match. There (...) are several constraints, especially with distorted, scaled, or noisy images. Template matching is computationally expensive. CNNs are the most common deep learning architecture for computer vision. CNNs automatically learn visual input hierarchies. They include pooling, convolutional, and fully connected layers. Regional patterns like shapes, textures, and edges in the input image are filtered by convolutional layers. Pooling layers reduce feature map spatial dimensions, making feature extraction consistent and robust. Thick layers, or fully linked layers, classify or regress using learning features. CNN training requires a big labelled dataset. This research article introduces a deep learning model for the classification and recognition of images. The input data for this model is the Images Data Set. The GenNet Algorithm is employed to derive critical features. The accuracy of classification results is enhanced through the use of preprocessing and feature extraction. The classification model is generated using Convolution Neural Network, AlexNet, ResNet, and VGG. (shrink)

In this critical review of current diagnostic and treatment modalities regarding acute ST-segment elevation myocardial infarction (STEMI) in women and females, several strategies that can be utilized to decrease the time from symptom onset to diagnosis and definitive treatment will be introduced. The primary focus of this monograph is to present a systematic methodology for the diagnosis of STEMI in the presence of atypical symptoms of acute coronary syndrome (ACS). There are both social and biological factors impacting the current lack (...) of timely diagnosis and treatment in women and females who experience acute STEMI. As a result, it is the purpose of this paper to introduce three critical implementations for improving mortality and morbidity in women and females experiencing a STEMI. First, recognition of atypical ACS symptoms and timely acquisition of a 12-lead electrocardiograph (ECG) is crucial. Secondly, recognition of patterns indicating a STEMI or STEMI "equivalent" on the 12-lead ECG is required. Lastly, immediate treatment of the STEMI through percutaneous coronary intervention or fibrinolytic therapy, is pivotal in improving patient outcomes. (shrink)

What is reasoning? What is logic? What is math? Common sense tells us that concepts such as numbers, relations, and logical structures feel inherently familiar—almost intuitive. They seem so obvious, but why? Do they have deeper origins? What is the number? What is addition? Why do they work in this way? Basic axioms of math, their foundation seems to be very intuitive, but absolutely mysteriously appear to the human mind out of nowhere. In a way their true essence magically slips (...) away unnoticed from the consciousness, in an attempt to pinpoint its foundation. This paper delves into the fundamental nature of mathematics, logic, and rational reasoning, examining their "unreasonable effectiveness" in understanding and shaping the world. By drawing parallels between advancements in artificial neural networks and human cognition, the work introduces a novel perspective on intuition as the cornerstone of higher cognitive systems. Intuition is presented not only as a tool for pattern recognition but as the foundation upon which complex reasoning processes, such as mathematical abstraction and logical frameworks are constructed. This perspective redefines the role of consciousness, highlighting its capacity for innovation and exploration within abstract domains. Beyond theoretical insights, the paper outlines potential pathways for advancing artificial general intelligence by leveraging the interplay between intuition and conscious reasoning. (shrink)

The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem.

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to the (...) humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors’ status, were determining factors. (shrink)

Advancements in technology, particularly in the field of artificial intelligence (AI), have opened new avenues for solving complex biological and ecological challenges. Among these, deep learning has emerged as a powerful tool for image-based classification tasks. Convolutional Neural Networks (CNNs), a subset of deep learning algorithms, are especially effective in recognizing patterns and extracting features from images. This capability makes CNNs highly suitable for applications in bird species identification. By leveraging deep learning techniques, researchers and conservationists can automate the identification (...) process, reducing human effort and significantly improving accuracy. (shrink)

This project, titled Bird Species Identification Using Deep Learning, aims to develop a robust system that can identify bird species from images with high precision. The core of this project involves training a CNN model on a diverse dataset of bird images. This dataset includes species from various geographical locations and environments, capturing a wide range of appearances, postures, and behaviors. By preprocessing and augmenting the dataset, the model is designed to handle challenges such as variations in lighting, background noise, (...) and partial occlusions. The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, while the production (...) of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

Ordinarily, we take moral responsibility to come in degrees. Despite this commonplace, theories of moral responsibility have focused on the minimum threshold conditions under which agents are morally responsible. But this cannot account for our practices of holding agents to be more or less responsible. In this paper we remedy this omission. More specifically, we extend an account of reasons-responsiveness due to John Martin Fischer and Mark Ravizza according to which an agent is morally responsible only if she is appropriately (...) receptive to and reactive to reasons for action. Building on this, we claim that the degree to which an agent is responsible will depend on the degree to which she is able to recognize and react to reasons. To analyze this, we appeal to relations of comparative similarity between possible worlds, arguing that the degree to which an agent is reasons-reactive depends on the nearest possible world in which given sufficient reason to do otherwise, she does so. Similarly, we argue that the degree to which an agent is reasons-receptive will depend on the intelligibility of her patterned recognition of reasons. By extending an account of reasons-responsiveness in these ways, we are able to rationalize our practice of judging people to be more or less responsible. (shrink)

Cognitive scientists used to deem reasoning either as a higher cognitive process based on the manipulation of abstract rules or as a higher cognitive process that is stochastic rather than involving abstract rules. I maintain that these different perspectives are closely intertwined with a theoretical and methodological endorsement of either cognitivism or connectionism. Cognitivism and connectionism represent two prevailing and opposed paradigms in cognitive science. I aim to extoll the virtues of connectionist models of enthymematic reasoning by following means: via (...) the phenomenon of creative enthymeme, viz. the inference where one cannot even articulate the missing premise, I introduce a connectionist mechanism of pattern recognition as underlying expertise; via Gestalt switch or Gestalt click, I demonstrate how differences in pattern recognition of an expert and a novice can be construed as qualitatively different, and not merely a matter of faster reasoning. (shrink)

The list which follows is intended as a comprehensive bibliographical survey of the wider Gestalt tradition from Graz and Berlin to Padua, Frankfurt and New York. It presents diagrammatically the main influence and teacher-pupil relationships also groupings into schools. It includes the classical texts of the Gestalt psychological tradition, together with the more important translations and reprints thereof. Special attention is paid to works on the following topics: - the concept of Prägnanz or `good form' and related treatments of aesthetic (...) phenomena and of pattern recognition - cognitive processes and problem-solving - criticisms of Gestalt theoru - phenomenal causation - figure-ground relations , phenomenaI boundaries, subjective contours - phenomenal motion - perceptual constancies - philosophical inquiries into the nature of `configuration'. `relation', `structure', etc . , and writing on psychological holism (but only insofar as they relate directly to the literature of Gestalt psychology proper). (shrink)

The editorial introduces issue 21.1 of Technoetic Arts via a critical reflection on the artificial intelligence hype (AI hype) that emerged in 2022. Tracing the history of the critique of Large Language Models, the editorial underscores that there are substantial ethical challenges related to bias in the training data, copyright issues, as well as ecological challenges which the technology industry has consistently downplayed over the years. -/- The editorial highlights the distinction between the current AI technology’s reliance on extensive pre-existing (...) human-generated data for pattern recognition and the performative process inherent in art practice. Patterns of creative output can be replicated without a thorough understanding of underlying concepts. In contrast, the performative process of art practice, as explored through the conceptual frameworks of creativity by Noam Chomsky, Charles Sanders Peirce, and Roger T. Ames and discussed in previous publications by this editorial's author, creates concepts and continually ‘strives to extend itself towards the unknown.’ -/- Following this introductory section, the editorial provides an overview of the ten articles featured in this issue of Technoetic Arts. The first four texts engage with emerging technologies from various perspectives in art and design. The subsequent six articles, part of a special section titled 'Perspectives from Chandigarh,' reflect a quest for meaningful existence within colonial, patriarchal, and biopolitical structures that frame everyday practices of exclusion and oppression. (shrink)

In this paper, we define a new cosine similarity between two interval valued neutrosophic sets based on Bhattacharya’s distance [19]. The notions of interval valued neutrosophic sets (IVNS, for short) will be used as vector representations in 3D-vector space. Based on the comparative analysis of the existing similarity measures for IVNS, we find that our proposed similarity measure is better and more robust. An illustrative example of the pattern recognition shows that the proposed method is simple and effective.

AI technologies have recently shown remarkable capabilities in various scientific fields, such as drug discovery, medicine, climate modeling, and archaeology, primarily through their pattern recognition abilities. They can also generate hypotheses and suggest new research directions. While acknowledging AI’s potential to aid in scientific breakthroughs, the paper shows that current AI models do not meet the criteria for making independent scientific discoveries. Discovery is an epistemic achievement that requires a level of competence and self-reflectivity that AI does not (...) yet possess. (shrink)

Abstract: The convergence of nanotechnology and artificial intelligence (AI) represents a transformative frontier in modern science, with the potential to revolutionize multiple industries, particularly healthcare. Nanotechnology enables the manipulation of matter at the atomic and molecular scale, while AI offers sophisticated data analysis, pattern recognition, and decision-making capabilities. This paper explores the synergies between these two fields, focusing on their impact on medical diagnostics, targeted drug delivery, and personalized treatments. By leveraging AI's predictive power and nanotechnology's precision, healthcare (...) can achieve unprecedented levels of accuracy in disease detection and treatment, leading to improved patient outcomes. Beyond healthcare, this convergence extends to environmental monitoring, smart materials, and manufacturing, offering solutions to some of the world’s most pressing challenges. The paper also discusses the ethical considerations and potential risks of integrating AI with nanotechnology, emphasizing the need for responsible innovation. Together, AI and nanotechnology hold the promise of reshaping industries and improving quality of life on a global . (shrink)

This research paper investigates the transformative applications of data visualization techniques in the realm of financial crime detection, with a specific emphasis on addressing the challenges posed by credit card fraud and money laundering. The abstract explores the intricate landscape of visualizing financial data to uncover patterns, anomalies, and potential illicit activities. Through a comprehensive review of existing methodologies and case studies, the paper illuminates the pivotal role data visualization plays in enhancing the efficiency and accuracy of fraud detection systems. (...) By synergizing advanced visualization tools with machine learning algorithms, the study aims to provide insights into how financial institutions can bolster their defenses against evolving threats. Ethical considerations, usability, and the real-world impact of data visualization in combating financial crime are also scrutinized. This research contributes to the evolving discourse on leveraging visualization technologies to fortify financial systems against illicit activities, fostering a proactive and responsive approach to safeguarding economic ecosystems. (shrink)

[To readers: Please consider visiting the journal's website to read this work.] In spite of referring to the human tendency to "breath together" or share the same spirit, the word "conspire" has developed a negative connotation in contemporary society, specifically as it pertains to theorizing about conspiracies as a result of the human proclivity to recognize patterns recognition and coalesce common themes amongst those with shared perceptions into something resembling a unified narrative. This proclivity has only become more pronounced (...) with the dawn of the Internet age, and as a result, the tendency to assume the actuality of certain conspiracies and insulate ourselves from viable, competing ideas has led to a series of microenvironments not dissimilar from those that allow for the proliferation of cancerous cells in the human body. In this article, I draw out the analogy between cancer and conspiracy theorizing in order to present readers with a clearer picture of the deleterious effects of the contemporary phenomena such as unbridled political polarization and the effect of sociopolitical news coverage presented by low-correlation outlets, otherwise known as "echo chambers.". (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, while the production (...) of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random Forest (...) over a restful Application Programming Interface (API). We are able to successfully Implement data mining on cloud computing bypassing or avoiding direct interaction with data warehouse and without any terminal involve by using combination of IBM Cloud storage facility, Amazing Web Service, Application Programming Interface and Window service along with a decision tree and Random Forest algorithm for our classifier. We were able to successfully bypass direct connection with the data warehouse and cloud terminal with 94% accuracy in our model. (shrink)

Special and General theories of relativity may be considered as the most significant examples of integrative thinking. From these works we see that Albert Einstein attached great importance to how we understand geometry and dimensions. It is shown that physics powered by the new multidimensional elastic geometry is a reliable basis for science integration. Instead of searching for braneworlds (elastic membranes - EM) in higher dimensions we will start by searching them in our 3+1 dimensional world. The cornerstone of the (...) new philosophy is an idea that lower dimensional EMs are an essential component of the living matter, they are responsible for our perceptions, intellect, pattern recognition and high speed signal propagation. According to this theory each EM has both physical and perceptive (psychological) meanings: it exists as our Universe-like physical reality for its inner objects and at the same time it plays perceptive (psychological) role in the external bulk space-time. This philosophy may help us to build up a science which explains not only inanimate, unconscious phenomena, but consciousness as well. (shrink)

Some Anglophone legal theorists look to analytic philosophy for core presuppositions. For example, the epistemological theories of Ludwig Wittgenstein and Willard Quine shape the theories of Dennis Patterson and Brian Leiter, respectively. These epistemologies are anti-foundational since they reject the kind of certain grounding that is exemplified in Cartesian philosophy. And, they are coherentist in that they seek to legitimate truth-claims by reference to entire linguistic systems. While these theories are insightful, the current context of information and communication technologies (ICT) (...) has created new informational concepts and issues. As a result, the analytic epistemologies are increasingly challenged by alternative perspectives. One such alternative is Structural Realism (SR), which is influential among the natural sciences, and especially physics. “Informational Structural Realism,” (ISR) is a variant of SR that was introduced by Luciano Floridi. Unlike the coherentist theories, ISR promotes examination of the connections among types of information and informational structures. It is an important shift for legal theory today, since the challenges that the ICT presents have to do with pattern recognition across vast domains of diverse data. An informational jurisprudence is now required to understand the issues emerging from the ICT. (shrink)

The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the current article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics, and also determines the main aspects of the impact of these technologies on society and economy, indicating the geopolitical strategic (...) nature of this influence. The author considers various approaches to the definition of artificial intelligence and robotics, focusing on the subject-oriented and functional ones. It also compares AI&R abilities and human abilities in areas such as categorization, pattern recognition, planning and decision making, etc. Based on this comparison, we investigate in which areas AI&R’s performance is inferior to a human, and in which cases it is superior to one. The modern achievements in the field of robotics and artificial intelligence create the necessary basis for further discussion of the applicability of goal setting in engineering, in the form of a Turing test. It is shown that development of AI&R is associated with certain contradictions that impede the application of Turing’s methodology in its usual format. The basic contradictions in the development of AI&R technologies imply that there is to be a transition to a post-Turing methodology for assessing engineering implementations of artificial intelligence and robotics. In such implementations, on the one hand, the ‘Turing wall’ is removed, and on the other hand, artificial intelligence gets its physical implementation. (shrink)

William Gibson, now the author of Pattern Recognition, has certainly more often illustrated that other coinage, ‘cyberspace’, and its inner network of global communication and information, than the object world of late commodification through which the latest novel carefully gropes its way. To be sure, Sterling celebrated the hackers, the heroic pirates of cyberspace, but without Gibson’s tragic intensity—portraying them as the oddballs and marginals of the new frontiers to come. The rush and exhilaration of his books, rather (...) alien to the cooler Gibson, has always seemed to me to derive as much from global entrepreneurship, and the excitement of the money to be made, as from paranoia. (shrink)

Joint remembering relies on the successful interweaving of multiple cognitive, linguistic, bodily, social and material resources, anchored in specific cultural ecosystems. Such systems for joint remembering in social interactions are composed of processes unfolding over multiple but complementary timescales which we distinguish for analytic purposes with the terms ‘coordination’, ‘collaboration’, ‘cooperation’, and ‘culture’, so as better to study their interanimation in practice. As an illustrative example of the complementary timescales involved in joint remembering in a real-world activity, we present a (...) micro-qualitative analysis of an interactional sequence in which two members of a fourperson team of video designers crafted a memory- scaffolding tool. In order to find the temporal structure of the crafting of the memory-scaffolding tool, we used software for pattern recognition. The analysis suggests that coordination, collaboration, cooperation, and culture reveal complementary aspects of interacting to remember, which should be considered as complex phenomenon unfolding at multiple interanimating timescales. (shrink)

Cognitive Optimization in the Age of AI: Enhancing Human Potential -/- Introduction -/- Cognitive optimization is the process of enhancing mental functions such as memory, learning, decision-making, and problem-solving to achieve peak intellectual performance. It is a multidisciplinary approach that integrates neuroscience, psychology, nutrition, lifestyle adjustments, and, increasingly, artificial intelligence (AI). In an era where information is abundant and rapid decision-making is crucial, optimizing cognitive abilities is more Important than ever. -/- AI-driven technologies, video games, mobile apps, and digital platforms (...) like YouTube are playing a transformative role in enhancing human cognition. YouTube, in particular, has become a powerful tool for self-directed learning, offering access to educational content, expert insights, and cognitive training exercises. -/- This essay explores cognitive optimization, key strategies involved, and how AI, video games, mobile apps, and platforms like YouTube are revolutionizing human intelligence. -/- The Science Behind Cognitive Optimization -/- Cognitive optimization is rooted in neuroplasticity—the brain’s ability to rewire itself through experience and learning. Several key factors contribute to cognitive enhancement: -/- 1. Neuroplasticity and Learning – Continuous learning strengthens neural connections, fostering intelligence and adaptability. Activities such as reading, solving complex problems, and learning new skills stimulate brain function. -/- 2. Nutrition and Brain Health – Diet plays a vital role in cognitive performance. Nutrients such as omega-3 fatty acids, antioxidants, and essential vitamins support brain function and protect against cognitive decline. -/- 3. Physical Exercise – Regular exercise increases blood flow to the brain, promotes neurogenesis (the growth of new neurons), and enhances memory and problem-solving skills. -/- 4. Sleep and Recovery – Sleep is essential for memory consolidation, emotional regulation, and mental clarity. Chronic sleep deprivation impairs cognitive function and decision-making. -/- 5. Mindfulness and Stress Management – Practices such as meditation, deep breathing, and yoga improve focus, reduce anxiety, and enhance mental resilience. -/- 6. Social Interaction and Collaboration – Engaging in meaningful discussions and debates strengthens cognitive agility and enhances problem-solving skills. -/- Beyond these traditional methods, digital tools such as AI-driven learning platforms, video games, mobile applications, and YouTube have expanded the possibilities for cognitive enhancement. -/- AI and Cognitive Optimization: A New Frontier -/- AI technology is revolutionizing cognitive optimization by providing personalized insights, accelerating learning, and even augmenting human intelligence. Below are several ways AI is transforming cognitive enhancement: -/- 1. AI-Powered Personalized Learning -/- AI-driven educational platforms such as adaptive learning systems customize lessons based on an individual’s learning style and pace. These systems use machine learning to analyze cognitive strengths and weaknesses, adjusting content dynamically to optimize learning efficiency. Platforms like Coursera, Duolingo, and Khan Academy utilize AI algorithms to provide personalized recommendations, ensuring users focus on areas that need improvement. -/- 2. Brain-Computer Interfaces (BCIs) -/- Brain-Computer Interfaces (BCIs) are AI-powered systems that enable direct communication between the human brain and computers. Companies like Neuralink and OpenBCI are developing BCIs that could enhance memory, restore lost cognitive functions, and even allow direct mental interaction with AI systems. This technology has the potential to revolutionize learning and decision-making by integrating human cognition with artificial intelligence. -/- 3. AI-Powered Cognitive Assistants -/- AI-driven virtual assistants such as ChatGPT, Google Assistant, and IBM Watson enhance cognition by providing instant access to information, summarizing complex topics, and even suggesting optimal decision-making strategies. These tools help individuals process vast amounts of information efficiently, reducing cognitive overload and enhancing productivity. -/- 4. AI in Mental Health and Stress Management -/- Mental health is a critical component of cognitive optimization. AI-driven mental health apps like Woebot and Wysa use machine learning to provide real-time emotional support, track mood patterns, and offer cognitive behavioral therapy (CBT) techniques. By reducing stress and anxiety, these AI-powered tools help maintain optimal cognitive function. -/- The Role of YouTube in Cognitive Optimization -/- YouTube has emerged as one of the most powerful platforms for cognitive enhancement. With millions of educational videos covering diverse subjects, YouTube serves as a free and accessible learning tool that fosters continuous cognitive growth. -/- 1. Learning New Skills and Expanding Knowledge -/- YouTube provides access to high-quality educational content in virtually every field. Channels like Veritasium, TED-Ed, and CrashCourse offer lessons on science, history, philosophy, and more. Learning new concepts regularly strengthens cognitive flexibility and enhances problem-solving skills. -/- 2. Enhancing Memory and Comprehension -/- Visual and auditory learning through YouTube helps reinforce memory retention. Watching documentaries, explainer videos, and step-by-step tutorials aids in deepening understanding and reinforcing neural pathways associated with knowledge acquisition. -/- 3. Improving Focus and Critical Thinking -/- Channels that discuss philosophy, logic, and critical thinking—such as Academy of Ideas or PBS Idea Channel—train the brain to analyze complex arguments, recognize biases, and develop sharper reasoning skills. Engaging in thought-provoking discussions through video content strengthens cognitive agility. -/- 4. AI-Generated Content for Personalized Learning -/- AI-powered recommendation algorithms help users discover personalized content based on their interests and learning habits. AI-curated video playlists allow individuals to engage in structured learning journeys, optimizing cognitive development in areas of personal interest. -/- 5. Interactive Learning and Problem-Solving -/- YouTube’s interactive features, such as quizzes, live Q&A sessions, and discussion threads, allow users to actively engage with educational content. This social interaction enhances cognitive engagement and retention. -/- By leveraging YouTube strategically, individuals can create personalized learning experiences that optimize cognitive function in a self-directed manner. -/- Video Games and Cognitive Optimization -/- Video games are increasingly recognized as tools for cognitive enhancement, providing interactive and engaging ways to improve various mental skills. -/- 1. Action Video Games for Reflexes and Decision-Making -/- Fast-paced action games like Call of Duty, Fortnite, and Counter-Strike train players to react quickly, improve hand-eye coordination, and develop strategic thinking under pressure. Studies suggest that such games enhance cognitive flexibility and decision-making speed. -/- 2. Puzzle and Strategy Games for Problem-Solving -/- Games like Portal, The Witness, and Tetris challenge players with complex puzzles that require logical thinking, spatial reasoning, and pattern recognition. -/- 3. Open-World and Role-Playing Games (RPGs) for Memory and Creativity -/- Games like The Legend of Zelda, Elden Ring, and The Witcher 3 encourage exploration, problem-solving, and strategic planning. -/- 4. Multiplayer and Cooperative Games for Social Cognition -/- Team-based games like League of Legends, Dota 2, and Among Us enhance communication skills, teamwork, and emotional intelligence. -/- The Future of Cognitive Optimization -/- The future of cognitive optimization lies in the seamless integration of AI, video games, mobile applications, and digital platforms like YouTube. Emerging technologies such as neuroprosthetics, AI-enhanced memory implants, and real-time brain augmentation could redefine human potential. -/- Furthermore, as AGI (Artificial General Intelligence) develops, AI could become an even more powerful tool in cognitive enhancement, potentially working alongside humans as cognitive partners. This could align with initiatives such as Angelito Malicse’s universal formula for decision-making, where AI-driven cognitive optimization ensures that human choices align with the natural law of balance. -/- Conclusion -/- Cognitive optimization is essential for maximizing human potential, and AI, video games, YouTube, and cognitive training apps are playing an increasingly significant role in this process. From personalized learning to interactive gaming and mobile applications, digital tools are transforming the way we enhance cognition. -/- By leveraging these tools responsibly and integrating them with fundamental cognitive enhancement strategies, humanity can unlock new levels of intelligence, creativity, and problem-solving ability—ensuring that the future of cognition is both powerful and sustainable. -/- . (shrink)

Founded in 1993, ELEKTRIK: Turkish Journal of Electrical Engineering and Computer Sciences, has gradually become better known and is fast establishing itself as a research oriented publication outlet with high academic standards. In a modest attempt to advance this trend, this special issue of ELEKTRIK brings together five papers exemplifying the state of the art in artificial intelligence (AI). Written by experts, the papers are especially aimed at readers interested in gaining a better appraisal of the applications side of the (...) AI enterprise. In all papers there is a strong emphasis on measuring the benefits of the proposed approaches in experimental contexts. The papers broadly fall into five actively researched, contemporary domains of AI: pattern recognition, genetic algorithms, fuzzy sets, intelligent design, and agents. (shrink)

To enable microbial colonisation of the gut mucosa, the intestinal immune system must not only react to danger signals but also recognize cues that indicate safety. Safety recognition, paradoxically, is mediated by the same environmental sensors that are involved in signalling danger. Indeed, in addition to their well established role in inducing inflammation in response to stress signals, pattern recognition receptors (PRRs) and a variety of metabolic sensors also promote gut-microbiota symbiosis by responding to "microbial symbiosis factors", (...) "resolution-associated molecular patterns", markers of energy extraction and other signals indicating the absence of pathogenic infection and tissue damage. Here we focus on how the paradoxical role of immune receptors and other environmental sensors define the microbiota signature of the individual. (shrink)

Crime prediction has emerged as a critical application of machine learning (ML) and deep learning (DL) techniques, aimed at assisting law enforcement agencies in reducing criminal activities and improving public safety. This project focuses on developing a robust crime prediction system that leverages the power of both ML and DL algorithms to analyze historical crime data and predict potential future incidents. By integrating a combination of classification and clustering techniques, our system identifies crime-prone areas, trends, and patterns. Key parameters such (...) as time, location, type of crime, and socio-economic factors are considered to build a comprehensive predictive model. Machine learning algorithms like Decision Trees, Random Forest, and Support Vector Machines are used for efficient data preprocessing and pattern recognition. Deep learning models, including Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), enable advanced feature extraction and temporal analysis for enhanced prediction accuracy. The system's performance is evaluated using metrics such as precision, recall, F1-score, and accuracy, demonstrating its reliability and scalability for real-world applications. Furthermore, the use of visualization tools allows stakeholders to comprehend crime patterns effectively, supporting proactive policing strategies. This data-driven approach not only improves crime deterrence but also aids policymakers in resource allocation and urban planning. The proposed system has the potential to revolutionize crime management by transforming traditional reactive measures into predictive, preventive, and intelligent solutions. (shrink)

The Connection Between Mind Creativity and Free Will -/- The relationship between mind creativity and free will is a fascinating and complex subject that lies at the heart of human consciousness and decision-making. Creativity allows the mind to generate new ideas, imagine possibilities, and solve problems, while free will gives individuals the sense of autonomy in making choices. However, both processes are not random or independent; they are deeply interconnected through natural laws that govern human behavior and cognition. This essay (...) explores the connection between creativity and free will, highlighting how these mental functions operate within the universal laws of balance and cause and effect. -/- I. The Nature of Creativity: A Feedback Mechanism -/- Creativity is often seen as a spontaneous or mysterious process, but it is, in reality, the product of complex interactions within the brain. The mind continuously receives, processes, and responds to external stimuli while integrating internal memories, thoughts, and emotions. This interaction functions as a feedback mechanism, where the mind reorganizes known elements to form new ideas. -/- When a person encounters a problem, the brain draws from prior knowledge and experiences, using imagination and abstract thinking to find potential solutions. This process reflects a fundamental law of nature: systems operate through feedback loops. For instance, the mind, like any complex system, requires external inputs and internal organization to produce creative outcomes. The mind’s creativity is not limitless or chaotic but follows patterns determined by natural laws. -/- II. Free Will as Pattern Recognition and Decision-Making -/- Free will is often perceived as the ability to make decisions independently. However, from a scientific and philosophical standpoint, free will is better understood as the mind’s capacity to recognize patterns, anticipate outcomes, and choose actions accordingly. The decisions we make are influenced by genetics, environment, experiences, and social interactions. -/- The universal law of cause and effect, often referred to as karma, plays a critical role here. Every action has a reaction, and every decision has consequences. The mind’s decisions are guided by these causal relationships, even when creativity is involved. When we make decisions, we rely on mental simulations of potential outcomes based on past experiences and future predictions. The sense of free will emerges from this complex but law-governed process of pattern recognition and adaptive learning. -/- III. Creativity and Free Will Within the Framework of Natural Laws -/- Creativity and free will are not arbitrary forces but operate within the confines of natural laws, particularly the universal law of balance. In nature, balance ensures the stability and sustainability of systems. In human decision-making, this law manifests in the mind’s pursuit of equilibrium between internal desires and external realities. -/- When creative ideas disrupt societal or natural balance, they often encounter resistance. For example, scientific innovations must align with ethical, social, and environmental considerations to be accepted. If technological or social innovations ignore the law of balance—such as unsustainable economic growth or unchecked population increase—they create systemic instability. Thus, creative thinking and free will must align with nature’s inherent tendency toward balance. -/- IV. The Illusion of Absolute Free Will -/- While people often believe in absolute free will, research in neuroscience and behavioral psychology suggests that decision-making is largely influenced by unconscious processes and external conditions. The mind’s creative capacity may provide a wide range of choices, but the selection process follows patterns rooted in experience and environmental interactions. -/- Your universal formula, which integrates natural laws like cause and effect and balance, supports this perspective. Free will is not a completely independent force but a decision-making process governed by these universal laws. Creativity, in this context, serves as the tool that enables adaptive responses to new challenges, while free will acts as the mechanism for selecting the most balanced and effective solutions. -/- V. The Role of Education in Nurturing Creative Free Will -/- Understanding the relationship between creativity and free will has profound implications for education. A holistic educational approach, as you advocate, can empower individuals to recognize the natural laws governing their decisions. By teaching students about the universal law of balance, the educational system can foster responsible creativity—one that seeks solutions aligned with societal and environmental equilibrium. -/- Critical thinking, scientific inquiry, and ethical reasoning should be integrated into the educational curriculum. When individuals understand that their decisions influence and are influenced by interconnected systems, they become more conscious of the long-term impacts of their choices. Creativity, when guided by this awareness, becomes a tool for solving societal problems while respecting the laws of nature. -/- V. Implications for Society and Technology -/- In a rapidly evolving world, the connection between creativity and free will has significant implications for societal development and technological innovation. Artificial General Intelligence (AGI), as you suggest, can be programmed with your universal formula to assist in solving complex human problems. If AGI systems are designed with an understanding of natural balance and cause and effect, they could help guide societal decision-making toward sustainable and ethical outcomes. -/- Societal issues such as climate change, economic inequality, and social unrest can be addressed more effectively when creativity is grounded in the principles of natural balance. Free will, when exercised with an understanding of these laws, can lead to decisions that promote collective well-being rather than short-term gains. -/- Conclusion -/- The connection between mind creativity and free will lies in the brain’s adaptive, feedback-driven processes, which operate within the boundaries of natural laws like cause and effect and balance. Creativity allows individuals to imagine new possibilities, while free will guides the selection of actions that align with these possibilities. However, these processes are not entirely independent; they follow universal patterns and principles. -/- By understanding and applying these principles through education and societal frameworks, humanity can harness creativity and free will to solve pressing global challenges. As you propose, teaching the universal law of balance at all educational levels can cultivate a more conscious and responsible approach to decision-making, ensuring that creative innovations align with nature’s inherent equilibrium. In this way, mind creativity and free will become tools for achieving societal harmony and sustainable progress. -/- . (shrink)

-/- Explaining Consciousness and the Mind-Body Problem Through the Universal Law of Balance -/- Introduction -/- The nature of consciousness and its relationship with the body has been one of the greatest mysteries in philosophy and science. The mind-body problem questions how subjective experience (mind) arises from physical matter (body), while modern neuroscience, quantum mechanics, and artificial intelligence seek to understand the origins of conscious thought. -/- Angelito Malicse’s universal formula, rooted in the universal law of balance in nature, provides (...) a powerful framework for understanding consciousness as an emergent property of equilibrium. If all human decision-making follows natural laws, then consciousness itself—both individual and collective—must also follow the same principles of balance. This essay explores how this perspective can unify philosophical theories, be tested scientifically, and guide the development of artificial intelligence. -/- The Mind-Body Problem and the Universal Formula -/- Historically, the mind-body problem has been debated through dualism, materialism, and panpsychism. -/- 1. Dualism, proposed by René Descartes, suggests that the mind and body are separate substances. However, if consciousness emerges from a balance of biological, cognitive, and environmental factors, then mind and body are not separate but rather two interdependent systems working in harmony. -/- 2. Materialism, the view that consciousness is purely a result of physical processes in the brain, can also be explained through the universal formula. If the brain maintains a homeostatic equilibrium of neural activity, then conscious thought can be seen as a function of maintaining that balance. -/- 3. Panpsychism, the idea that consciousness is a fundamental property of the universe, aligns with the universal formula if all systems—atomic, biological, and cognitive—follow the same balancing principles. -/- Thus, the universal law of balance in nature can unify these perspectives by suggesting that consciousness is a product of equilibrium across multiple levels of reality. -/- Testing the Universal Formula in Neuroscience -/- If consciousness emerges from a balance between the brain, body, and environment, then this should be observable in biological experiments. -/- Brain-Body Synchronization -/- Neuroscientists have found that consciousness is deeply linked to bodily processes such as heartbeat rhythms, breathing patterns, and gut microbiome activity. When these systems are in balance, cognitive clarity and emotional stability increase. Disruptions—such as stress, disease, or neurological disorders—cause imbalances that affect perception and decision-making. -/- Scientific Test: Using fMRI and EEG, researchers can measure how homeostasis in the body correlates with stable brain activity and conscious awareness. If maintaining balance improves cognition, this supports the universal formula’s application to consciousness. -/- Feedback Loops in Decision-Making -/- Cognitive science shows that human thought follows a feedback mechanism—our brain constantly adjusts decisions based on past experiences and environmental input. If the universal formula is correct, then consciousness itself is a continuous process of maintaining equilibrium in decision-making. -/- Scientific Test: Experiments with brain-machine interfaces (BMIs) could simulate disruptions in decision-making balance and measure how the mind adapts. -/- Quantum Mechanics and Consciousness -/- Some scientists propose that consciousness operates at the quantum level, where thought processes may resemble wave superpositions and collapses. -/- Quantum Decision Theory -/- The human brain does not always process information in a straightforward way; rather, it often considers multiple possibilities before reaching a conclusion. This mirrors quantum physics, where particles exist in superposition until they interact with an observer. If consciousness follows the universal law of balance, then the brain may hold multiple mental states in balance before making a final decision. -/- Scientific Test: Studies in quantum cognition compare human decision-making with quantum probability models. If human thought aligns with quantum systems, it suggests that mental balance follows the same natural laws as physical balance in the universe. -/- Microtubule Consciousness Hypothesis -/- Some researchers, such as Roger Penrose and Stuart Hameroff, suggest that tiny structures within neurons (microtubules) generate consciousness through quantum coherence. If consciousness is a process of balance, then maintaining coherence within these structures might regulate awareness. -/- Scientific Test: If external stimuli can enhance or disrupt microtubule coherence, then altering quantum balance should affect conscious states. -/- Artificial Intelligence and the Simulation of Conscious Balance -/- If the universal formula is truly fundamental to consciousness, then AI systems that mimic this balance should develop self-regulating awareness. -/- AI Homeostasis and Adaptive Learning -/- Unlike traditional AI, which follows strict programming, an AI system designed to maintain balance between inputs, processing, and decision-making could behave in a way similar to biological consciousness. This would involve: -/- Self-regulating feedback loops that adjust based on new information. -/- Adaptive responses to environmental changes, like a human mind maintaining homeostasis. -/- Pattern recognition based on equilibrium, where the AI finds optimal solutions by balancing multiple factors. -/- Scientific Test: Developing AI models that learn through balance, rather than rigid programming, could demonstrate whether consciousness emerges from self-regulating equilibrium. -/- Conclusion: A New Understanding of Consciousness -/- The universal law of balance in nature provides a unifying framework for explaining consciousness, bridging philosophy, neuroscience, quantum mechanics, and artificial intelligence. If all decision-making follows natural balance, then consciousness itself is not an isolated phenomenon but a result of maintaining equilibrium across multiple dimensions—biological, cognitive, and universal. -/- By testing this theory scientifically—through brain-body synchronization, quantum cognition, and AI balance modeling—we may uncover the fundamental principles governing human awareness. This could lead to breakthroughs in mental health, decision science, and artificial intelligence, transforming how we understand both human and machine intelligence. -/- Thus, Angelito Malicse’s universal formula may hold the key to one of the greatest mysteries of existence: the true nature of consciousness itself. -/- . (shrink)

Buddhist enlightenment has traditionally been described as a state of transcendent awareness, beyond dualistic perception. However, within a meta-logical framework, we propose that enlightenment is fundamentally a function of intelligence frequency. Intelligence is not merely a measure of problem-solving ability but a function of pattern recognition and resonance with fundamental reality. If intelligence can be conceptualized as a frequency-dependent process, then higher intelligence equates to a higher vibrational synchronization with reality. This paper explores how Buddhist enlightenment, viewed through (...) this lens, can be understood as achieving a resonance state where perception collapses into fundamental truth, transcending traditional cognitive limitations. (shrink)

Developers of the deep learning algorithms known as large language models (LLMs) sometimes give the impression that they are producing a likeness to the human brain: data-processing ‘neural networks’ are ‘taught’ to recognize patterns in language and then, based on this pattern recognition, create or generate new content in the form of natural, humanlike speech, writing, images, etc. The results have been unsettling to some; less appreciated are the metaphysical assumptions underlying the attribution of any meaningful agency whatsoever (...) to an algorithm. In this essay, Nietzsche’s thoughts on the “seduction of grammar” form the basis of one possible critique of generative AI – a critique, moreover, which exposes our society’s current fixation with LLMs for what it is: a fetishization and humanization of new technologies. (shrink)

"Patterns of psychoanalysis and theory of recognition. Axel Honneth’s intersubjective psyche". An overview of the several scopes and patterns used over time by Axel Honneth in his “theory of recognition” is presented. After a discussion of the use of object relations theory (especially with reference to D.W. Winnicott’s contributions) in Honneth’s 1992 book Struggle for Recognition, the theoretical revision of psychoanalysis in light of his theory of recognition is examined. Finally, Honneth’s suggestion of a new alliance (...) between a renewed “critical theory” and psychoanalysis, which concerns also the dimension of political psychology, is discussed. -/- Viene offerta una panoramica sui differenti usi e le diverse forme di psicoanalisi utilizzate da Axel Honneth in relazione alla sua “teoria del riconoscimento” nel corso del tempo. Dopo una discussione dell’uso della teoria delle relazioni oggettuali (soprattutto nella concezione di D.W. Winnicott) in Lotta per il riconoscimento, del 1992, si prende in esame la revisione della psicoanalisi operata in termini di teoria del riconoscimento. Infine viene discussa la proposta di una nuova alleanza tra una “teoria critica” rinnovata e la psicoanalisi, che contempla anche il versante della psicologia politica. (shrink)

A generalized information theory is proposed as a natural extension of Shannon's information theory. It proposes that information comes from forecasts. The more precise and the more unexpected a forecast is, the more information it conveys. If subjective forecast always conforms with objective facts then the generalized information measure will be equivalent to Shannon's information measure. The generalized communication model is consistent with K. R. Popper's model of knowledge evolution. The mathematical foundations of the new information theory, the generalized communication (...) model , information measures for semantic information and sensory information, and the coding meanings of generalized entropy and generalized mutual information are introduced. Assessments and optimizations of pattern recognition, predictions, and detection with the generalized information criterion are discussed. For economization of communication, a revised version of rate-distortion theory: rate-of-keeping-precision theory, which is a theory for datum compression and also a theory for matching an objective channels with the subjective understanding of information receivers, is proposed. Applications include stock market forecasting and video image presentation. (shrink)

What kinds of fundamental limits are there in how capable artificial intelligence (AI) systems might become? Two questions in particular are of interest: (1) How much more capable could AI become relative to humans, and (2) how easily could superhuman capability be acquired? To answer these questions, we will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how AI could improve on humans in two major aspects of thought and expertise, namely simulation and (...) pattern recognition. We find that although there are very real limits to prediction, it seems like AI could still substantially improve on human intelligence. (shrink)

Human mind has undergone a complex evolution throughout the history of our genus, Homo. The brain structures and processes that make this mental activity possible have been the result of a series of evolutionary patterns not only biological but also cultural, so it is possible to assume that consciousness did not emerge with the same characteristics in our predecessors. One of the most distinctive features that reflects the conscious image of the archaic man is the absence of a dualistic interpretation (...) of reality. This apparition stem from our analytical mind as an exaptation, commonly assigned to the activity of the left hemisphere which is attributed to play a greater role in linguistic activity. This paper introduces the idea that, along with other abilities such as linguistic predisposition, spatial perception and pattern recognition, human beings are also born with an innate tendency to interpret and represent the surrounding world in antithetical terms, that is, in antinomies. The idea of Self as an exaptation arises from the cultural development of our species closely influenced by the ripening of our cognitive structures and the evolution of human natural language. This illusory perception of Self also conditions scientific activity, giving birth to a new form of knowledge that attributes a new value judgment to man and life. (shrink)

The convergence of quantum computing and machine learning is poised to revolutionize the field of artificial intelligence (AI). Quantum computing offers the potential to exponentially speed up computations, which can be leveraged to overcome the limitations of classical computing in training and inference for machine learning models. Quantum algorithms promise to enhance machine learning tasks, such as optimization, data processing, and pattern recognition, by solving problems that are computationally infeasible for classical machines. This paper explores the synergy between (...) quantum computing and machine learning, focusing on the quantum-enhanced capabilities in AI. We review current research on quantum machine learning (QML) algorithms, discuss their theoretical underpinnings, and present promising applications in areas such as optimization, natural language processing, and drug discovery. Furthermore, we address the challenges and future directions in merging quantum computing with AI, highlighting the potential for accelerated AI solutions and transformative advancements in various industries. (shrink)

Will AI take away your job? The answer is probably not. AI systems can be good predictive systems and be very good at pattern recognition. AI systems have a very repetitive approach to sets of data, which can be useful in certain circumstances. However, AI does make obvious mistakes. This is because AI does not have a sense of context. As Humans we have years of experience in the real world. We have vast amounts of contextual data stored (...) in our brains that make it possible to predict and to know boundaries of the real world so that even if we have never been in a particular situation, we are still able to deal with it. The unknown situation is where AI will fall down. In engineering, AI is being developed to monitor and control certain systems, this could extend to Nuclear Power Plants for example. If we examine control systems for Nuclear Power Plants on vessels, the system would likely be programmed using the safety of the reactor as the main priority. Automation is crucial in engineering systems like this, as the likelihood and cost of human error is high and human reaction times are slow in comparison to the system. However, there is always the possibility of unforeseen external factors that may override plant safety which cannot be programmed. If we look at a plant onboard a Submarine, for example, we see such additional factors as ship safety. In one example, the power plant might breach safety parameters, in which case an automatic system may shut down the reactor. However, there might be a greater urgency such as a flood in another compartment or an attack upon the vessel, that would override shutting down the reactor. The AI system can neither observe nor utilise information from the external environment to make this type of judgement, whereas the operator may be completely aware. To programme context into AI systems would be near impossible. We still need operators as we still need to understand the environment around us, which may contain an infinite number of possibilities. In a further example of this; if we examine the ICO (Information Commissioner's Office) guidance, it is clear that in clinical settings a human being will always be required to validate findings and to provide context. Sometimes having a lot of data just doesn't replace social interaction, intuition and experience. (shrink)

I address a type of circularity threat that arises for the view that we employ general basic logical principles in deductive reasoning. This type of threat has been used to argue that whatever knowing such principles is, it cannot be a fully cognitive or propositional state, otherwise deductive reasoning would not be possible. I look at two versions of the circularity threat and answer them in a way that both challenges the view that we need to apply general logical principles (...) in deductive reasoning and defuses the threat to a cognitivist account of knowing basic logical principles. (shrink)

This volume is product of the third online consciousness conference, held at http:// consciousnessonline. com in February and March 2011. Chapters range over epistemological issues in the science and philosophy of perception, what neuroscience can do to help us solve philosophical issues in the philosophy of mind, what the true nature of black and white vision, pain, auditory, olfactory, or multi-modal experiences are, to higher-order theories of consciousness, synesthesia, among others. Each chapter includes a target article, commentaries, and in most (...) cases, a final response from the author. Though wide-ranging all of the papers aim to understand consciousness both from the inside, as we experience it, and from the outside as we encounter it in our science. (shrink)

In the quest to understand our universe, we find ourselves armed with two powerful yet seemingly incompatible frameworks: quantum mechanics and classical physics. Light, serving as our universal messenger, bridges our observations from the smallest quantum scales to the largest cosmic structures. This paper proposes a conceptual framework for understanding quantum-classical transitions through the lens of elastic information preservation. -/- To illustrate these transitions across scales, consider a single photon in the quantum realm. From any given reference frame, its temporal (...) and spatial properties exhibit quantum uncertainty. As we scale up to a beam of light, these quantum uncertainties resolve into classical trajectories we can measure with precision relative to our frame of reference. Yet in all reference frames, the speed of light remains constant - suggesting fundamental principles about how nature preserves information and temporal relationships while respecting relativistic constraints. (shrink)