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This paper analyzes Agi poetry and utilizes the Panayanon concept of power called gahum as its critical framework. Philippine gay literature unfurled after the publication of Ladlad: An Anthology of Philippine Gay Writing (1994) and continues to reach higher grounds. However, gay criticism has been too focused on the discourse of the Manila bakla and not much has been said about indigenous models of queerness in the regions. As agi is an indigenous articulation of homosexuality in Panay in Central Philippines, this paper traces the connection of the agi's attendant performance (kaagian) with the indigenous tradition of babaylanism. By investigating the strong presence of babaylanic imagery in agi poetry, this study attempts to unravel the connection of kaagian with a precolonial form of power called gahum, which is deeply attuned to the animist spatiality of Panay. The babaylan is a shaman, culture bearer, and political leader that embodies physical and spiritual gahum that go beyond the human realm. By exploring the interconnected concepts of kaagian, gahum, and babaylanism, this critical study reveals that agi writers champion the image of the babaylan to subvert colonial-imposed hegemonies and decolonize the agi identity. [ABSTRACT FROM AUTHOR]

This paper examines the toponymic heritage used in Kenya's Authoritative Geographic Information (AGI) toponyms database of 26,600 gazetteer records through documentation and characterization of meanings of place names in topographic mapping. A comparison was carried out between AGI and GeoNames and between AGI and OpenStreetMap (OSM) volunteered records. A total of 15,000 toponymic matchings were found. Out of these, 1567 toponyms were then extracted for further scrutiny using AGI data in the historical records and from respondents on toponyms' meanings. Experts in toponymy assisted in verifying these data. From the questionnaire responses, 235 names occurred in more than one place while AGI data had 284. The elements used to characterize the toponyms included historical perceptions of heritage evident in toponyms in their localities, ethnographic, toponymical and morphology studies on Kenya's dialects. There was no significant relationship established between the same place name usages among dialects as indicated by a positive weak correlation r (438), = 0.166, p < 0.001 based on the effect of using the related places and the distance between related places. The weak correlation implies that the one name one place principle does not apply due to diverse language boundaries, strong bonds associated with historical toponyms in the form of heritage and significant variations on how names resist changes to preserve their heritage. [ABSTRACT FROM AUTHOR]

The evolution and civilization development lead us to the progress next important step - the creation of AGI. More "intelligent" tasks are successfully solved by machine learning methods using neural network algorithms. Not only the solved problems quantitative increase in the number and accuracy are important, but also a qualitative transition to the tasks of obtaining "truly" new knowledge and building "truly" new goals on their basis. This transition can serve as a criterion for determining AGI. The paper shows necessity of using existing knowledge to advance into the field of more and more diverse "truly" new knowledge. Also, the paper shows usefulness of implementing proposed ideas on a scalable hierarchical structure which has two main modes of operation: "intuition" and "thinking", and structure of vector control of these and other operation modes, similar to animal hormonal control. [ABSTRACT FROM AUTHOR]

Trust is believed to be a foundational cornerstone for artificial intelligence (AI). In April 2019 the European Commission High Level Expert Group on AI adopted the Ethics Guidelines for Trustworthy AI, stressing that human beings will only be able to confidently and fully reap the benefits of AI if they can trust the technology. Trustworthy AI is defined as ethical, lawful and robust AI. Three things strike me about the EC Guidelines. Firstly, though building trust in AI seems to be a shared aim, it is not explicated what trust is, and how it can be built and maintained. Secondly, the Guidelines ignore the widespread distinction made in philosophical literature between trust and reliance. Thirdly, it is not clear how the values have been selected with which AI has to align and what would happen if they came into conflict. In this paper, I shall provide a conceptual analysis of trust in contrast to reliance and ask when it is warranted to talk about trust in AI and trustworthy AI. I shall show how trust and risk are related and what benefits and risks are associated with narrow and general AI. Also, I shall point out that metaphorical talk about ethically aligned AI ignores the real disagreements we have about ethical values. [ABSTRACT FROM AUTHOR]

This paper introduces a facile and effective route to decorate micro-sized silver particle surfaces with Ag/AgI nanoclusters through a wet chemical reaction at room temperature using iodine and ethanol as reactant and solvent, respectively. Photosensitivity of AgI is utilized in the route, and AgI decomposes into Ag upon contact with sunshine, forming Ag/AgI nanoclusters. The modified micro-sized Ag particles showed sinterability even at 200°C and formed rigid electrical conductive networks at 350°C. Moreover, sintered film containing the modified Ag particles reached the best conductivity, 9.35 mΩ/sq, after sintering at 350°C for 20 min, while the film with untreated control Ag particles obtained its best conductivity at 400°C. The excellent sinterability should be attributed to the nanoclusters which served as a sintering aid during the heating process. However, increase of sintering temperature and time destroyed densification and conductivity of the sintered film containing the modified particles. [ABSTRACT FROM AUTHOR]

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This study investigates the strategic decision-making abilities of large language models (LLMs) via the game of Tic-Tac-Toe, renowned for its straightforward rules and definitive outcomes. We developed a mobile application coupled with web services, facilitating gameplay among leading LLMs, including Jurassic-2 Ultra by AI21, Claude 2.1 by Anthropic, Gemini-Pro by Google, GPT-3.5-Turbo and GPT-4 by OpenAI, Llama2-70B by Meta, and Mistral Large by Mistral, to assess their rule comprehension and strategic thinking. Using a consistent prompt structure in 10 sessions for each LLM pair, we systematically collected data on wins, draws, and invalid moves across 980 games, employing two distinct prompt types to vary the presentation of the game's status. Our findings reveal significant performance variations among the LLMs. Notably, GPT-4, GPT-3.5-Turbo, and Llama2 secured the most wins with the list prompt, while GPT-4, Gemini-Pro, and Mistral Large excelled using the illustration prompt. GPT-4 emerged as the top performer, achieving victory with the minimum number of moves and the fewest errors for both prompt types. This research introduces a novel methodology for assessing LLM capabilities using a game that can illuminate their strategic thinking abilities. Beyond enhancing our comprehension of LLM performance, this study lays the groundwork for future exploration into their utility in complex decision-making scenarios, offering directions for further inquiry and the exploration of LLM limits within game-based frameworks. [ABSTRACT FROM AUTHOR]

This paper outlines the experimental framework for an e-governance study by the AGI Laboratory. The goal of this research study is to identify indications of the relative performance of e-governance methodologies and how those methods might be improved by applying advanced agent and collective based AI software. The agent in this study will be based on the Independent Core Observer Model Cognitive Architecture modified with mASI (mediated Artificial Superintelligence) collective system architecture. The study will apply different groups and methods to a static set of questions analyzing the quality of those results. We hope to identify the best application model for e-governance using this kind of technology and help us identify additional paths for research with the mASI research program and systems as applied to e-governance. [ABSTRACT FROM AUTHOR]

This paper shows how the Independent Core Observer Model (ICOM) Cognitive Architecture for Artificial General Intelligence (AGI) can be applied to building a collective intelligence system called a mediated Artificial Superintelligence (mASI). The details include breaking down the ICOM implementation in the form of the mASI system and the general performance of initial studies with the mASI. Details of the primary difference between the Independent Core Observer Model Cognitive Architecture and the mASI architecture variant include inserting humanity in the contextual engine components of ICOM, creating a type of collective intelligence. Humans can 'mediate' new system-generated thinking keeping the thought process accessible and slow enough for humans to oversee and understand. This also allows the modification of emotional valences of the thought process of the mASI system to help the system generate complex contextual models (knowledge graphs) of new ideas and which speeds up the learning process. With the humans acting as control rods in a reactor and emotional drivers, the mASI system maintains safety where the system would cease to function if humans walked away. [ABSTRACT FROM AUTHOR]

Landgrebe and Smith (2022) have recently offered an important mathematical argument against the possibility of Artificial General Intelligence (AGI): human intelligence is a complex system; complex systems have some properties that cannot be modelled mathematically; hence we have no viable way to build an AI that would be able to emulate human intelligence. The issue of complexity is thus at the heart of the Landgrebe and Smith approach, and they tackle this issue by postulating a set of conditions, derived from mathematics, for a system to be complex. I argue that Hayek's "Theory of Complex Phenomena" offers an interesting alternative path to understanding what makes complex systems complex. This offers an argument complementary to that of Landgrebe and Smith, which approaches the issue of complexity from an ontological angle, and which is designed to show that AI systems are not the right kind of entity that may interact meaningfully with complex systems. [ABSTRACT FROM AUTHOR]

This paper articulates the methodology and reasoning for how biasing in the Independent Core Observer Model (ICOM) Cognitive Architecture for Artificial General Intelligence (AGI) is done. This includes the use of a forced western emotional model, the system "needs" hierarchy, fundamental biasing and the application of SSIVA theory at the high level as a basis for emotionally bound ethical and moral experience in ICOM systems and how that is manifested in system behavior and the mathematics that supports that experience or qualia in ICOM based systems. [ABSTRACT FROM AUTHOR]

In this paper, CeO 2 microplates were synthesized by a sol-gel auto-combustion method. AgI nanoparticles (NPs) were then deposited onto the surface of CeO 2 via a facile deposition–precipitation method. The as-prepared AgI/CeO 2 samples were characterized by various analytical techniques. The composites exhibited superior photocatalytic activities for the organic dyes (RhB) and the refractory pollutant (tetracycline (TC), a typical antibiotic) degradation under visible light irradiation. The CA-19.03 sample exhibited the highest photocatalytic activity. The enhanced photocatalytic performance could be ascribed to the improved separation of photogenerated charge carriers due to well-matched band structure. [ABSTRACT FROM AUTHOR]

The impact of complexity within government and societal systems is considered relative to the limitations of human cognitive bandwidth, and the resulting reliance on cognitive biases and systems of automation when that bandwidth is exceeded. Examples of how humans and societies have attempted to cope with the growing difference between the rate at which the complexity of systems and human cognitive capacities increase respectively are considered. The potential of and urgent need for systems capable of handling the existing and future complexity of systems, utilizing greater cognitive bandwidth through scalable AGI, are also considered, along with the practical limitations and considerations in how those systems may be deployed in real-world conditions. Several paradoxes resulting from the influence of prolific Narrow Tool AI systems manipulating large portions of the population are also noted. [ABSTRACT FROM AUTHOR]

Photocatalytic degradation, as a very significant advanced oxidation technology in the field of environmental purification, has attracted extensive attention in recent years. The design and synthesis of catalysts with high-intensity photocatalytic properties have been the focus of many researchers in recent years. In this contribution, two new supramolecular materials {[(L1)·(Ag4I7)]CH3CN} (1), {[(L2)·(Ag4I7)]CH3CN} (2) were synthesized by solution volatilization reaction of two cationic templates 1,3,5-Tris(4-aminopyridinylmethyl)-2,4,6-Trimethylphenyl bromide (L1) and 1,3,5-Tris(4-methyl pyridinyl methyl)-2,4,6-trimethylphenyl bromide (L2) with metal salt AgI at room temperature, respectively. The degradation effect of 1 and 2 as catalyst on tetracycline (TC) under visible light irradiation was studied. The results showed that the degradation of TC by 1 was better than that by 2 and both of them had good stability and cyclability. The effects of pH value, catalyst dosage, and anion in water on the photocatalytic performance were also investigated. The adsorption kinetics fit the quasi-first-order model best. After 180 min of irradiation with 1, the degradation rate of TC can reach 97.91%. In addition, the trapping experiments showed that ·OH was the main active substance in the photocatalytic degradation of TC compared with ·O2− and h+. Because of its simple synthesis and high removal efficiency, catalyst 1 has potential value for the treatment of wastewater containing organic matter. [ABSTRACT FROM AUTHOR]

Fitting a bionically inspired cognitive model to a technical application domain is a challenging task. This work presents the fundamental steps in applying the SiMA-based cognitive model ECABA to the domain of building automation. The focus of the paper is to show the initial steps and challenges for implementing the human inspired mechanisms of drives and social rules when modeling a cognitive control system for a non-human body. We then illustrate the flexibility and extensibility of the intended distributed cognitive approach by presenting the iterative development of a simple reactive system with interacting components. Using a simple use case, we show how the cognitive processes can be implemented and utilized in a multi-agent system to provide a first, reactivity-based control system. [ABSTRACT FROM AUTHOR]

Most Artificial Intelligence (AI) implementations so far are based on the exploration of how the human brain is designed. Nevertheless, while significant progress is shown on specialized tasks, creating an Artificial General Intelligence (AGI) remains elusive. This manuscript proposes that instead of asking how the brain is constructed, the main question should be how it was evolved. Since neurons can be understood as intelligent agents, intelligence can be thought of as a construct of multiple agents working and evolving together as a society, within a long-term memory and evolution context. More concretely, we suggest placing Multiple Neighborhood Cellular Automata (MNCA) on a blockchain with an interaction protocol and incentives to create an AGI. Given that such a model could become a "strong" AI, we present the conjecture that this infrastructure is possible to simulate the properties of cognition as an emergent phenomenon. [ABSTRACT FROM AUTHOR]

Endgame studies have long served as a tool for testing human creativity and intelligence. We find that they can serve as a tool for testing machine ability as well. Two of the leading chess engines, Stockfish and Leela Chess Zero (LCZero), employ significantly different methods during play. We use Plaskett's Puzzle, a famous endgame study from the late 1970s, to compare the two engines. Our experiments show that Stockfish outperforms LCZero on the puzzle. We examine the algorithmic differences between the engines and use our observations as a basis for carefully interpreting the test results. Drawing inspiration from how humans solve chess problems, we ask whether machines can possess a form of imagination. On the theoretical side, we describe how Bellman's equation may be applied to optimize the probability of winning. To conclude, we discuss the implications of our work on artificial intelligence (AI) and artificial general intelligence (AGI), suggesting possible avenues for future research. [ABSTRACT FROM AUTHOR]

Methods of improving the state and rate of progress within the domain of philosophy using collective intelligence systems are considered. By applying mASI systems superintelligence, debiasing, and humanity’s current sum of knowledge may be applied to this domain in novel ways. Such systems may also serve to strongly facilitate new forms and degrees of cooperation and understanding between different philosophies and cultures. The integration of these philosophies directly into their own machine intelligence seeds as cornerstones could further serve to reduce existential risk while improving both ethical quality and performance. [ABSTRACT FROM AUTHOR]

This paper aims to identify the systemic factors contributing to the transformation of the moral identity/moral identities of nowadays person(s), during these times of technological changes and challenges, based on the rhizomality and transgressiveness, in order to formulate some logic and clear questions related to the possibility of moral identity/moral identities of AIs/AGIs.

Despite the recent progress in AI powered by deep learning in solving narrow tasks, we are not close to human intelligence in its flexibility, versatility, and efficiency. Efficient learning and effective generalization come from inductive biases, and building Artificial General Intelligence (AGI) is an exercise in finding the right set of inductive biases that make fast learning possible while being general enough to be widely applicable in tasks that humans excel at. To make progress in AGI, we argue that we can look at the human brain for such inductive biases and principles of generalization. To that effect, we propose a strategy to gain insights from the brain by simultaneously looking at the world it acts upon and the computational framework to support efficient learning and generalization. We present a neuroscience-inspired generative model of vision as a case study for such approach and discuss some open problems about the path to AGI. [ABSTRACT FROM AUTHOR]

Artificial general intelligence (AGI) progression metrics indicate AGI will occur within decades. No proof exists that AGI will benefit humans and not harm or eliminate humans. A set of logically distinct conceptual components is proposed that are necessary and sufficient to (1) ensure various AGI scenarios will not harm humanity, and (2) robustly align AGI and human values and goals. By systematically addressing pathways to malevolent AI we can induce the methods/axioms required to redress them. Distributed ledger technology (DLT, "blockchain") is integral to this proposal, e.g., "smart contracts" are necessary to address the evolution of AI that will be too fast for human monitoring and intervention. The proposed axioms: (1) Access to technology by market license. (2) Transparent ethics embodied in DLT. (3) Morality encrypted via DLT. (4) Behavior control structure with values at roots. (5) Individual bar-code identification of critical components. (6) Configuration Item (from business continuity/disaster recovery planning). (7) Identity verification secured via DLT. (8) "Smart" automated contracts based on DLT. (9) Decentralized applications--AI software modules encrypted via DLT. (10) Audit trail of component usage stored via DLT. (11) Social ostracism (denial of resources) augmented by DLT petitions. (12) Game theory and mechanism design. [ABSTRACT FROM AUTHOR]

Rhamnogalacturonan I (RGI) is a pectic polysaccharide composed of a backbone of alternating rhamnose and galacturonic acid residues with side chains containing galactose and/or arabinose residues. The structure of these side chains and the degree of substitution of rhamnose residues are extremely variable and depend on species, organs, cell types and developmental stages. Deciphering RGI function requires extending the current set of monoclonal antibodies (mAbs) directed to this polymer. Here, we describe the generation of a new mAb that recognizes a heterogeneous subdomain of RGI. The mAb, INRA-AGI-1, was produced by immunization of mice with RGI oligosaccharides isolated from potato tubers. These oligomers consisted of highly branched RGI backbones substituted with short side chains. INRA-AGI-1 bound specifically to RGI isolated from galactan-rich cell walls and displayed no binding to other pectic domains. In order to identify its RGI-related epitope, potato RGI oligosaccharides were fractionated by anionexchange chromatography. Antibody recognition was assessed for each chromatographic fraction. INRA-AGI-1 recognizes a linear chain of (1→4)-linked galactose and (1→5)-linked arabinose residues. By combining the use of INRA-AGI-1 with LM5, LM6 and INRA-RU1 mAbs and enzymatic pre-treatments, evidence is presented of spatial differences in RGI motif distribution within individual cell walls of potato tubers and carrot roots. These observations raise questions about the biosynthesis and assembly of pectin structural domains and their integration and remodeling in cell walls. [ABSTRACT FROM AUTHOR]

Nowadays, surveillance cameras are widely installed in public places for security and law enforcement, but the video quality may be low because of the limited transmission bandwidth and storage capacity. In this study, the authors proposed a gait recognition method for extremely low‐quality videos, which have a frame‐rate at one frame per second (1 fps) and resolution of 32 × 22 pixels. Different from popular temporal reconstruction‐based methods, the proposed method uses the average gait image (AGI) over the whole sequence as the appearance‐based feature description. Based on the AGI description, the authors employed a large number of weak classifiers to reduce the generalisation errors. The performance can be further improved by incorporating the model‐based information into the classifier ensemble. The authors found that the performance improvement is directly proportional to the average disagreement level of weak classifiers (i.e. diversity), which can be increased by using the model‐based information. The authors evaluated the proposed method on both indoor and outdoor databases (i.e. the low‐quality versions of OU‐ISIR‐D and USF databases), and the results suggest that our method is more general and effective than other state‐of‐the‐art algorithms. [ABSTRACT FROM AUTHOR]

The formation phenomena of silver carbonate (Ag2CO3)–silver iodide (AgI) solid solutions were investigated by X-ray diffraction, thermogravimetry-differential thermal analysis, and electrical conductivity measurement. Results revealed that AgI and Ag2CO3 reacted with each other when mixed at room temperature. The reaction products were classified into three types: (1) AgI-based solid solutions in the AgI-rich region for x = 10% or less in x Ag2CO3–(1 − x) AgI; (2) Ag2CO3-based solid solutions in the Ag2CO3-rich region for x = 60% or more; and (3) silver carbonate iodides in the intermediate range for x between 10% and 60%. For the AgI-based solid solutions, the incorporation of Ag2CO3 into the AgI lattice expanded the unit cell and enhanced electrical conductivity. The solubility limit of Ag2CO3 into the AgI lattice estimated from the differential thermal analysis was x ≈ 5%. [ABSTRACT FROM AUTHOR]

Diabetes mellitus, a group of metabolic disorders characterized by hyperglycemia, is one of the most serious and common diseases around the world and is associated with major complications such as diabetic neuropathy, retinopathy, and cardiovascular diseases. A widely used treatment for non-insulin-dependent diabetes is α-glucosidase inhibitors (AGIs) such as acarbose, which hinders hydrolytic cleavage of disaccharides and retard glucose absorption. The ability to inhibit α-glucosidase activity has been reported in leaf and fruit of pepper (Capsicum annuum L.). In this study, we aimed to identify quantitative trait loci (QTLs) controlling α-glucosidase inhibitory activity (AGI activity) in pepper leaf and fruit using enzyme assay and genotyping-by-sequencing (GBS) analysis. The AGI activity at three stages of leaf and one stage of fruit development was analyzed by 96 F2 individuals. GBS analysis identified 17,427 SNPs that were subjected to pepper genetic linkage map construction. The map, consisting of 763 SNPs, contained 12 linkage groups with a total genetic distance of 2379 cM. QTL analysis revealed seven QTLs (qAGI1.1, qAGI11.1, qAGI5.1, qAGI9.1, qAGI12.1, qAGI5.2, and qAGI12.2) controlling AGI activity in pepper leaf and fruit. The QTLs for AGI activity varied by plant age and organ. This QTL information is expected to provide a significant contribution to developing pepper varieties with high AGI activity. [ABSTRACT FROM AUTHOR]

An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of a dataset for machine learning by an AI entity. Datasets can be very expensive to purchase, as, depending on both the proper selection of the elements and the homogeneity of the data contained within, constructing and maintaining the integrity of a dataset is difficult. Blockchain as a highly secure storage medium presents a technological quantum leap in maintaining data integrity. Furthermore, blockchain's immutability constructs a fruitful environment for creating high quality, permanent and growing datasets for deep learning. The combination of AI and blockchain could impact fields like Internet of things (IoT), identity, financial markets, civil governance, smart cities, small communities, supply chains, personalized medicine and other fields, and thereby deliver benefits to many people. [ABSTRACT FROM AUTHOR]