Results for 'artificial language'

948 found
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  1. The Role of Artificial Languages.Martin Stokhof - 2011 - In Gillian Russell Delia Graff Fara (ed.), The Routledge Companion to Philosophy of Language. New York: Routledge. pp. 5440553.
    When one looks into the role of artificial languages in philosophy of language it seems appropriate to start with making a distinction between philosophy of language proper and formal semantics of natural language. Although the distinction between the two disciplines may not always be easy to make since there arguably exist substantial historical and systematic relationships between the two, it nevertheless pays to keep the two apart, at least initially, since the motivation commonly given for the (...)
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  2. In Conversation with Artificial Intelligence: Aligning language Models with Human Values.Atoosa Kasirzadeh - 2023 - Philosophy and Technology 36 (2):1-24.
    Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is conversational agents, which output natural language text in response to prompts and queries. This mode of engagement raises a number of social and ethical questions. For example, what does it mean to align conversational agents with human norms or values? Which norms or values should they be aligned with? And how can this be accomplished? (...)
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  3. Integrating Multiple Intelligence and Artificial Intelligence in Language Learning: Enhancing Personalization and Engagement.Edgar Eslit - 2023 - Preprints.
    This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, (...)
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  4. Beyond Consciousness in Large Language Models: An Investigation into the Existence of a "Soul" in Self-Aware Artificial Intelligences.David Côrtes Cavalcante - 2024 - Https://Philpapers.Org/Rec/Crtbci. Translated by David Côrtes Cavalcante.
    Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a (...)
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  5. Artificial Speech and Its Authors.Philip J. Nickel - 2013 - Minds and Machines 23 (4):489-502.
    Some of the systems used in natural language generation (NLG), a branch of applied computational linguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams’ account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence embedded (...)
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  6. Boring language is constraining the impact of climate science.Quan-Hoang Vuong, Minh-Hoang Nguyen & Viet-Phuong La - 2024 - Ms Thoughts.
    Language, one of humanity’s major transformative innovations, is foundational for many cultural, artistic, scientific, and economic advancements, including the creation of artificial intelligence (AI). However, in the fight against climate change, the power of such innovation is constrained due to the boring language of climate science and science communication. In this essay, we encapsulated the situation and risks of boring language in communicating climate information to the public and countering climate denialism and disinformation. Based on the (...)
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  7. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions.Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith & Simone Stumpf - 2024 - Information Fusion 106 (June 2024).
    As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from (...)
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  8. Understanding Artificial Agency.Leonard Dung - forthcoming - Philosophical Quarterly.
    Which artificial intelligence (AI) systems are agents? To answer this question, I propose a multidimensional account of agency. According to this account, a system's agency profile is jointly determined by its level of goal-directedness and autonomy as well as is abilities for directly impacting the surrounding world, long-term planning and acting for reasons. Rooted in extant theories of agency, this account enables fine-grained, nuanced comparative characterizations of artificial agency. I show that this account has multiple important virtues and (...)
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  9. Artificial Intelligence and Analytic Pragmatism / Umjetna inteligencija i analitički pragmatizam (Bosnian translation by Nijaz Ibrulj).Nijaz Ibrulj & Robert B. Brandom - 2022 - Sophos 1 (15):201-222.
    The text "Artificial Intelligence and Analytic Pragmatism" was translated from the book by Robert B. Brand: Between Saying and Doing: Towards an Analytical Pragmatism. Chapter 3. Oxford University Press. pp. 69 - 92.
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  10. Artificial Intelligence in Higher Education in South Africa: Some Ethical Considerations (14th edition).Tanya de Villiers-Botha - forthcoming - Kagisano.
    There are calls from various sectors, including the popular press, industry, and academia, to incorporate artificial intelligence (AI)-based technologies in general, and large language models (LLMs) (such as ChatGPT and Gemini) in particular, into various spheres of the South African higher education sector. Nonetheless, the implementation of such technologies is not without ethical risks, notably those related to bias, unfairness, privacy violations, misinformation, lack of transparency, and threats to autonomy. This paper gives an overview of the more pertinent (...)
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  11. AI language models cannot replace human research participants.Jacqueline Harding, William D’Alessandro, N. G. Laskowski & Robert Long - 2024 - AI and Society 39 (5):2603-2605.
    In a recent letter, Dillion et. al (2023) make various suggestions regarding the idea of artificially intelligent systems, such as large language models, replacing human subjects in empirical moral psychology. We argue that human subjects are in various ways indispensable.
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  12. Artificial Intelligence and Punjabi Culture.D. P. Singh - 2023 - International Culture and Art (Ica) 5 (4):11-14.
    Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. AI works by training machines to learn from data and experiences. Such devices can recognize patterns, understand spoken language, see and understand images, and even make predictions based on their learning. Voice assistants like Siri or Alexa can understand our voice commands, answer questions, and perform tasks for us. AI-based self-driving cars can sense their surroundings, make decisions, and (...)
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  13. Toward biologically plausible artificial vision.Mason Westfall - 2023 - Behavioral and Brain Sciences 46:e290.
    Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision – found in reinforcement-learning agents navigating artificial three-dimensional environments – can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents’ performance, lending some indirect support to the language-of-thought hypothesis (LoTH).
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  14. Artificial Leviathan: Exploring Social Evolution of LLM Agents Through the Lens of Hobbesian Social Contract Theory.Gordon Dai, Weijia Zhang, Jinhan Li, Siqi Yang, Chidera Ibe, Srihas Rao, Arthur Caetano & Misha Sra - manuscript
    The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior explorations of LLM agent design, our work introduces a simulated agent society where complex social relationships dynamically form and evolve over time. Agents are imbued with psychological drives and placed in a sandbox survival environment. We conduct an evaluation of the agent society through the lens of Thomas Hobbes's seminal Social Contract Theory (...)
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  15. Artificial Intelligence for the Internal Democracy of Political Parties.Claudio Novelli, Giuliano Formisano, Prathm Juneja, Sandri Giulia & Luciano Floridi - 2024 - Minds and Machines 34 (36):1-26.
    The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, (...)
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  16. Artificial Intelligence and Its Impact on Punjabi culture.Devinder Pal Singh - 2023 - Punjab Dey Rang, Lahore, Pakistan 17 (3):5-10.
    Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. It is a rapidly evolving field with ongoing research and development to advance its capabilities and address its limitations. AI has permeated various aspects of our daily lives, and its applications can be found in numerous products and services. The integration of AI continues to expand across multiple sectors, providing convenience, personalization, and efficiency in our daily lives. While Punjabi (...)
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  17. Action and Agency in Artificial Intelligence: A Philosophical Critique.Justin Nnaemeka Onyeukaziri - 2023 - Philosophia: International Journal of Philosophy (Philippine e-journal) 24 (1):73-90.
    The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language and (...)
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  18. Large Language Models and Biorisk.William D’Alessandro, Harry R. Lloyd & Nathaniel Sharadin - 2023 - American Journal of Bioethics 23 (10):115-118.
    We discuss potential biorisks from large language models (LLMs). AI assistants based on LLMs such as ChatGPT have been shown to significantly reduce barriers to entry for actors wishing to synthesize dangerous, potentially novel pathogens and chemical weapons. The harms from deploying such bioagents could be further magnified by AI-assisted misinformation. We endorse several policy responses to these dangers, including prerelease evaluations of biomedical AIs by subject-matter experts, enhanced surveillance and lab screening procedures, restrictions on AI training data, and (...)
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  19. Machine Advisors: Integrating Large Language Models into Democratic Assemblies.Petr Špecián - forthcoming - Social Epistemology.
    Could the employment of large language models (LLMs) in place of human advisors improve the problem-solving ability of democratic assemblies? LLMs represent the most significant recent incarnation of artificial intelligence and could change the future of democratic governance. This paper assesses their potential to serve as expert advisors to democratic representatives. While LLMs promise enhanced expertise availability and accessibility, they also present specific challenges. These include hallucinations, misalignment and value imposition. After weighing LLMs’ benefits and drawbacks against human (...)
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  20. Defining Generative Artificial Intelligence: An Attempt to Resolve the Confusion about Diffusion.Raphael Ronge, Markus Maier & Benjamin Rathgeber - manuscript
    The concept of Generative Artificial Intelligence (GenAI) is ubiquitous in the public and semi-technical domain, yet rarely defined precisely. We clarify main concepts that are usually discussed in connection to GenAI and argue that one ought to distinguish between the technical and the public discourse. In order to show its complex development and associated conceptual ambiguities, we offer a historical-systematic reconstruction of GenAI and explicitly discuss two exemplary cases: the generative status of the Large Language Model BERT and (...)
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  21. Ethics of Artificial Intelligence.Stefan Buijsman, Michael Klenk & Jeroen van den Hoven - forthcoming - In Nathalie Smuha (ed.), Cambridge Handbook on the Law, Ethics and Policy of AI. Cambridge University Press.
    Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the (...)
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  22. Classification of Sign-Language Using MobileNet - Deep Learning.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (7):29-40.
    Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this (...)
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  23. Enhancing Education with Artificial Intelligence: The Role of Intelligent Tutoring Systems.Ahmad Marouf, Rami Al-Dahdooh, Mahmoud Jamal Abu Ghali, Ali Osama Mahdi, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Engineering and Information Systems (IJEAIS) 8 (8):10-16.
    Abstract: The integration of Artificial Intelligence (AI) into educational technology has revolutionized learning through Intelligent Tutoring Systems (ITS). These systems harness AI to deliver personalized, adaptive instruction that caters to individual student needs, thereby enhancing learning outcomes and engagement. This paper explores the evolution and impact of ITS, highlighting key AI technologies such as machine learning, natural language processing, and adaptive algorithms that underpin their functionality. By examining various case studies and applications, the paper illustrates how ITS have (...)
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  24. Artificial Agency and the Game of Semantic Extension.Fossa Fabio - 2021 - Interdisciplinary Science Reviews 46 (4):440-457.
    Artificial agents are commonly described by using words that traditionally belong to the semantic field of organisms, particularly of animal and human life. I call this phenomenon the game of semantic extension. However, the semantic extension of words as crucial as “autonomous”, “intelligent”, “creative”, “moral”, and so on, is often perceived as unsatisfactory, which is signalled with the extensive use of inverted commas or other syntactical cues. Such practice, in turn, has provoked harsh criticism that usually refers back to (...)
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  25. Imagination, Creativity, and Artificial Intelligence.Peter Langland-Hassan - 2024 - In Amy Kind & Julia Langkau (eds.), Oxford Handbook of Philosophy of Imagination and Creativity. Oxford University Press.
    This chapter considers the potential of artificial intelligence (AI) to exhibit creativity and imagination, in light of recent advances in generative AI and the use of deep neural networks (DNNs). Reasons for doubting that AI exhibits genuine creativity or imagination are considered, including the claim that the creativity of an algorithm lies in its developer, that generative AI merely reproduces patterns in its training data, and that AI is lacking in a necessary feature for creativity or imagination, such as (...)
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  26. Artificial Intelligence: Machine Translation Accuracy in Translating French-Indonesian Culinary Texts.Hasyim Muhammad - 2021 - International Journal of Advanced Computer Science and Applications 12 (3):186-191.
    The use of machine translation as artificial intelligence (AI) keeps increasing and the world’s most popular a translation tool is Google Translate (GT). This tool is not merely used for the benefits of learning and obtaining information from foreign languages through translation but has also been used as a medium of interaction and communication in hospitals, airports and shopping centres. This paper aims to explore machine translation accuracy in translating French-Indonesian culinary texts (recipes). The samples of culinary text were (...)
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  27. Are we at the start of the artificial intelligence era in academic publishing?Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Ruining Jin & Tam-Tri Le - 2023 - Science Editing 10 (2):1-7.
    Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making use (...)
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  28. Natural Language Understanding: Methodological Conceptualization.Vitalii Shymko - 2019 - Psycholinguistics 25 (1):431-443.
    This article contains the results of a theoretical analysis of the phenomenon of natural language understanding (NLU), as a methodological problem. The combination of structural-ontological and informational-psychological approaches provided an opportunity to describe the subject matter field of NLU, as a composite function of the mind, which systemically combines the verbal and discursive structural layers. In particular, the idea of NLU is presented, on the one hand, as the relation between the discourse of a specific speech message and the (...)
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  29. ITS for Data Manipulation Language (DML) Commands Using SQLite.Mahmoud Jamal Abu Ghali & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):57-92.
    In many areas, technology has facilitated many things, diagnosing diseases, regulating traffic and teaching students in schools rely on Intelligent systems to name a few. At present, traditional classroom-based education is no longer the most appropriate in schools. From here, the idea of intelligent e-learning for students to increase their culture and keep them updated in life began. E-learning has become an ideal solution, relying on artificial intelligence, which has a footprint in this through the development of systems based (...)
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  30. A Case for AI Consciousness: Language Agents and Global Workspace Theory.Simon Goldstein & Cameron Domenico Kirk-Giannini - manuscript
    It is generally assumed that existing artificial systems are not phenomenally conscious, and that the construction of phenomenally conscious artificial systems would require significant technological progress if it is possible at all. We challenge this assumption by arguing that if Global Workspace Theory (GWT) — a leading scientific theory of phenomenal consciousness — is correct, then instances of one widely implemented AI architecture, the artificial language agent, might easily be made phenomenally conscious if they are not (...)
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  31. Reid on the priority of natural language.John Turri - 2011 - Canadian Journal of Philosophy 41 (S1):214-223.
    Thomas Reid distinguished between natural and artificial language and argued that natural language has a very specific sort of priority over artificial language. This paper critically interprets Reid's discussion, extracts a Reidian explanatory argument for the priority of natural language, and places Reid's thought in the broad tradition of Cartesian linguistics.
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  32.  81
    Deadly Language Games: Theological Reflections on Emerging Reproductive Technologies.Nicholas Colgrove - 2024 - Christian Bioethics 30 (2):67-84.
    This issue of Christian Bioethics explores theological, metaphysical, and ethical questions surrounding emerging reproductive technologies. Narratives concerning such technologies are often manipulated via “language games.” Language games involve toying with language to ensure that one’s vision of the good gains or retains political prominence. Such games are common in academic discussions of “artificial womb” technologies. Abortion proponents, for example, are already using language to dehumanize subjects within “artificial wombs.” This is unsurprising. Were relevant subjects (...)
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  33. MODES OF LANGUAGE ACQUISITION AND COMMUNICATION.Varanasi Ramabrahmam - 2012 - In In the Proceedings of waves conference at Boston, USA, July 13-15, 2012.
    Four modes of language acquisition and communication are presented translating ancient Indian expressions on human consciousness, mind, their form, structure and function clubbing with the Sabdabrahma theory of language acquisition and communication. The modern scientific understanding of such an insight is discussed. . A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension and communication process forming the basis to develop software for relevantmind-machine modeling will be presented. The (...)
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  34. AI and Alien Languages.Matti Eklund - manuscript
    In this paper, I focus on AIs as very different, or at least potentially very different, kinds of language users from what humans are. Is the metasemantics for AI language use different, in the way Cappelen and Dever argue? Is it reasonable to think that AIs will come to use languages importantly different from human languages, what I call alien languages?
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  35. The Rising Tide of Artificial Intelligence in Scientific Journals: A Profound Shift in Research Landscape.Ricardo Grillo - 2023 - European Journal of Therapeutics 29 (3):686-688.
    Dear Editors, -/- I found the content of your editorials to be highly intriguing [1,2]. Scientific journals are witnessing a growing prevalence of publications related to artificial intelligence (AI). Three letters to the editor were recently published in your journal [3-5]. The renowned journal Nature has dedicated approximately 25 publications solely to the subject of ChatGPT. Moreover, a quick search on Pubmed using the term "ChatGPT" yields around 900 articles, with the vast majority originating in 2023. These statistics underscore (...)
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  36. Are Large Language Models "alive"?Francesco Maria De Collibus - manuscript
    The appearance of openly accessible Artificial Intelligence Applications such as Large Language Models, nowadays capable of almost human-level performances in complex reasoning tasks had a tremendous impact on public opinion. Are we going to be "replaced" by the machines? Or - even worse - "ruled" by them? The behavior of these systems is so advanced they might almost appear "alive" to end users, and there have been claims about these programs being "sentient". Since many of our relationships of (...)
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  37. Boguslawski's Analysis of Quantification in Natural Language.John-Michael Kuczynski - 2010 - Journal of Pragmatics 42 (10):2836-2844.
    The semantic rules governing natural language quantifiers (e.g. "all," "some," "most") neither coincide with nor resemble the semantic rules governing the analogues of those expressions that occur in the artificial languages used by semanticists. Some semanticists, e.g. Peter Strawson, have put forth data-consistent hypotheses as to the identities of the semantic rules governing some natural-language quantifiers. But, despite their obvious merits, those hypotheses have been universally rejected. In this paper, it is shown that those hypotheses are indeed (...)
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  38. Wittgenstein on critique of language.Mudasir A. Tantray - 2018 - International Journal of Creative Research Thoughts 6 (1):5-9.
    This paper tries to determine the philosophical nature of language, its functions, structure and content. It also explains the concept of natural language, ordinary and ideal language i.e. how there is a need of artificial perfect logical language without errors and unclearness in that language. This paper further shows the logical form of language with its syntactical, semantical, innate and acquired criteria for the evaluation of the languages. It deals with the analysis of (...)
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  39. Classification of Sign-Language Using Deep Learning by ResNet.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (8):25-34.
    American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the (...)
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  40. Large Language Models: Assessment for Singularity.R. Ishizaki & Mahito Sugiyama - manuscript
    The potential for Large Language Models (LLMs) to attain technological singularity—the point at which artificial intelligence (AI) surpasses human intellect and autonomously improves itself—is a critical concern in AI research. This paper explores the feasibility of current LLMs achieving singularity by examining the philosophical and practical requirements for such a development. We begin with a historical overview of AI and intelligence amplification, tracing the evolution of LLMs from their origins to state-of-the-art models. We then proposes a theoretical framework (...)
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  41. Pseudo Language and the Chinese Room Experiment: Ability to Communicate using a Specific Language without Understanding it.Abolfazl Sabramiz - manuscript
    The ability to communicate in a specific language like Chinese typically indicates that the speaker understands the language. A counterexample to this belief is John Searle’s Chinese room experiment. It has been shown in this experiment that in certain circumstances we can communicate with a Chinese speaker without intuitively acknowledging that the Chinese language is understood in the conversation. In the present paper, we aim to present another counterexample showing that, in certain circumstances, we can communicate using (...)
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  42. The History and Prehistory of Natural-Language Semantics.Daniel W. Harris - 2017 - In Sandra Lapointe & Christopher Pincock (eds.), Innovations in the History of Analytical Philosophy. London, United Kingdom: Palgrave-Macmillan. pp. 149--194.
    Contemporary natural-language semantics began with the assumption that the meaning of a sentence could be modeled by a single truth condition, or by an entity with a truth-condition. But with the recent explosion of dynamic semantics and pragmatics and of work on non- truth-conditional dimensions of linguistic meaning, we are now in the midst of a shift away from a truth-condition-centric view and toward the idea that a sentence’s meaning must be spelled out in terms of its various roles (...)
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  43. Simulative reasoning, common-sense psychology and artificial intelligence.John A. Barnden - 1995 - In Martin Davies & Tony Stone (eds.), Mental Simulation: Evaluations and Applications. Blackwell. pp. 247--273.
    The notion of Simulative Reasoning in the study of propositional attitudes within Artificial Intelligence (AI) is strongly related to the Simulation Theory of mental ascription in Philosophy. Roughly speaking, when an AI system engages in Simulative Reasoning about a target agent, it reasons with that agent’s beliefs as temporary hypotheses of its own, thereby coming to conclusions about what the agent might conclude or might have concluded. The contrast is with non-simulative meta-reasoning, where the AI system reasons within a (...)
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  44. Introduction: Philosophy and Theory of Artificial Intelligence.Vincent C. Müller - 2012 - Minds and Machines 22 (2):67-69.
    The theory and philosophy of artificial intelligence has come to a crucial point where the agenda for the forthcoming years is in the air. This special volume of Minds and Machines presents leading invited papers from a conference on the “Philosophy and Theory of Artificial Intelligence” that was held in October 2011 in Thessaloniki. Artificial Intelligence is perhaps unique among engineering subjects in that it has raised very basic questions about the nature of computing, perception, reasoning, learning, (...)
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  45. The language of thought as a logically perfect language.Andrea Bianchi - 2020 - In Vincenzo Idone Cassone, Jenny Ponzo & Mattia Thibault (eds.), Languagescapes. Ancient and Artificial Languages in Today's Culture. pp. 159-168.
    Between the end of the nineteenth century and the first twenty years of the twentieth century, stimulated by the impetuous development of logical studies and taking inspiration from Leibniz's idea of a characteristica universalis, the three founding fathers of the analytic tradition in philosophy, i.e., Frege, Russell, and Wittgenstein, started to talk of a logically perfect language, as opposed to natural languages, all feeling that the latter were inadequate to their (different) philosophical purposes. In the second half of the (...)
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  46.  65
    Mind and Machine: A Philosophical Examination of Matt Carter’s “Minds & Computers: An Introduction to the Philosophy of Artificial Intelligence”.R. L. Tripathi - 2024 - Open Access Journal of Data Science and Artificial Intelligence 2 (1):3.
    In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. Carter contrasts (...)
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  47. Elements of Cognitive Sciences and Artificial Intelligence in Gayatri Mantra.Varanasi Ramabrahmam - 2006 - In Ramabrahmam Varanasi (ed.), Proceedings of National seminar on Bharatiya Heritage in Engineering and Technology, May 11-13, 2006, at Department of Metallurgy and Inorganic Chemistry, I.I.Sc., Bangalore, India. pp. 249-254.
    The syllables and series of sounds composing Gayatri Mantra, and the sense and meaning attached to them are analyzed using Upanishadic Wisdom, Advaitha Philosophy and Sabdabrahma Siddhanta. The physical structure of mind as revealed by this analysis is presented. An insight of various phases of mind, their rise and set, their significance and implications to cognitive sciences and natural language comprehension branch of artificial intelligence are discussed. The possible applications of such an insight in the fields of cognitive (...)
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  48. In Pursuit of the Functional Definition of a Mind: The Inevitability of the Language Ontology.Vitalii Shymko - 2018 - Psycholinguistics 23 (1):327-346.
    In this article, the results of conceptualization of the definition of mind as an object of interdisciplinary applied research are described. The purpose of the theoretical analysis is to generate a methodological discourse suitable for a functional understanding of the mind in the context of the problem of natural language processing as one of the components of developments in the field of artificial intelligence. The conceptual discourse was realized with the help of the author's method of structural-ontological analysis, (...)
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  49. Revelation and Artificial Neural Networks.Lascelles G. B. James - manuscript
    The grammatical forms and material of the book of Revelation suggest a complex interplay of Old Testament and 1st century literature and language. As well, the book does not lack its own peculiarity and character that is unparalleled in the literate world. Various analytical tools including historical-comparative methodologies have been employed to reconstruct the linguistic paradigm of the book. Artificial intelligence and its derivatives provide alternate methods of probing this paradigm.
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  50. The Presidential Address: Where Demonstratives Meet Vagueness: Possible Languages.Adam Morton - 1999 - Proceedings of the Aristotelian Society 99 (1):1 - 18.
    I present three invented languages, in order to support a claim that vagueness and demonstrativity are related. One of them handles vagueness like English handles demonstratives, the second handles demonstratives like English handles vagueness, and the third combines the resources of the first two. The argument depends on the claim that all three can be learned and used by anyone who can speak English.
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