Results for 'Deep work'

982 found
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  1. Different researchers’ opinion based survey: On the insights and the beliefs’ regarding the existence of God in various religions to the atheistic belief with ‘no presence of God at all’.Deep Bhattacharjee - manuscript
    If this can be seen as a long way from the beginning of the ancient history, where humans have envisioned different new things and then invented them to make their life’s working smoother and easier, then it can be found that they have attributed their discoveries to various aspects and names of Gods and tried to signify their belief in the form of portraying the God’s powers through the nature of their discovery. Rather, in much modern times, when humans have (...)
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  2. Deep Brain Stimulation, Authenticity and Value.Pugh Jonathan, Maslen Hannah & Savulescu Julian - 2017 - Cambridge Quarterly of Healthcare Ethics 26 (4):640-657.
    Deep brain stimulation has been of considerable interest to bioethicists, in large part because of the effects that the intervention can occasionally have on central features of the recipient’s personality. These effects raise questions regarding the philosophical concept of authenticity. In this article, we expand on our earlier work on the concept of authenticity in the context of deep brain stimulation by developing a diachronic, value-based account of authenticity. Our account draws on both existentialist and essentialist approaches (...)
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  3. Deep Disagreement in Mathematics.Andrew Aberdein - 2023 - Global Philosophy 33 (1):1-27.
    Disagreements that resist rational resolution, often termed “deep disagreements”, have been the focus of much work in epistemology and informal logic. In this paper, I argue that they also deserve the attention of philosophers of mathematics. I link the question of whether there can be deep disagreements in mathematics to a more familiar debate over whether there can be revolutions in mathematics. I propose an affirmative answer to both questions, using the controversy over Shinichi Mochizuki’s work (...)
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  4. Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules.Phillip H. Kieval & Oscar Westerblad - manuscript
    We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful (...)
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  5. Deep Adaptation: Navigating the Realities of Climate Chaos.Jem Bendell & Rupert Read (eds.) - 2021 - Cambridge, UK & Medford, MA: Polity Press.
    Deep adaptation’ refers to the personal and collective changes that might help us to prepare for – and live with – a climate-influenced breakdown or collapse of our societies. It is a framework for responding to the terrifying realization of increasing disruption by committing ourselves to reducing suffering while saving more of society and the natural world. This is the first book to show how professionals across different sectors are beginning to incorporate the acceptance of likely or unfolding societal (...)
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  6. Arrogance and deep disagreement.Andrew Aberdein - 2020 - In Alessandra Tanesini & Michael P. Lynch (eds.), Polarisation, Arrogance, and Dogmatism: Philosophical Perspectives. London, UK: Routledge. pp. 39-52.
    I intend to bring recent work applying virtue theory to the study of argument to bear on a much older problem, that of disagreements that resist rational resolution, sometimes termed "deep disagreements". Just as some virtue epistemologists have lately shifted focus onto epistemic vices, I shall argue that a renewed focus on the vices of argument can help to illuminate deep disagreements. In particular, I address the role of arrogance, both as a factor in the diagnosis of (...)
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  7. Fogelin’s Theory of Deep Disagreements: A Relativistic Reading.Victoria Lavorerio - 2020 - Philosophical Investigations 43 (4):346-362.
    In “The Logic of Deep Disagreements,” Robert Fogelin claims that parties to a deep disagreement lack the common ground needed for arguments to work, making the disagreement impervious to rational resolution. Although Fogelin’s article received numerous responses, there has been no attempt to elucidate the epistemological theory behind Fogelin’s theses. In this article, I examine Fogelin’s theory of deep disagreements in light of his broader philosophy. The picture that emerges is that of relativism of distance, à (...)
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  8. Some ethics of deep brain stimulation.Joshua August Skorburg & Walter Sinnott Armstrong - 2020 - In Dan J. Stein & Ilina Singh (eds.), Global Mental Health and Neuroethics. Elsevier. pp. 117-132.
    Case reports about patients undergoing Deep Brain Stimulation (DBS) for various motor and psychiatric disorders - including Parkinson’s Disease, Obsessive Compulsive Disorder, and Treatment Resistant Depression - have sparked a vast literature in neuroethics. Questions about whether and how DBS changes the self have been at the fore. The present chapter brings these neuroethical debates into conversation with recent research in moral psychology. We begin in Section 1 by reviewing the recent clinical literature on DBS. In Section 2, we (...)
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  9. (1 other version)Is deep ecology inapplicable in African context: a conversation with Fainos Mangena.Diana-Abasi Ibanga - 2017 - Filosofia Theoretica: Journal of African Philosophy, Culture and Religions 6 (2):101-119.
    In 2015, Fainos Mangena published an essay entitled “How Applicable is the Idea of Deep Ecology in the African Context?” where he presented a number of arguments to support his thesis that deep ecology as discussed in the West has no place in the African context. Mangena later presented a counter-version of deep ecology that he claims is based on African philosophy. In this paper, I interrogated Mangena’s arguments for rejecting deep ecology and found that they (...)
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  10. Innovation, Deep Decarbonization and Ethics.Ewan Kingston - 2022 - Ethics, Policy and Environment 25 (3):375-384.
    Deep decarbonization – slashing global greenhouse gas emissions to net-zero – now dominates global climate policy. Two recent books assess feasible routes to achieve deep decarbonization. Bill Gates’ How to Avoid a Climate Disaster explains in depth why deep decarbonization requires significant innovations in tech, and Danny Cullenward and David Victor’s Making Climate Policy Work emphasizes the importance of policy innovation (beyond carbon pricing) for driving clean tech breakthroughs. In this critical review essay, I summarize and (...)
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  11. Diagnosis of Pneumonia Using Deep Learning.Alaa M. A. Barhoom & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):48-68.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is (...)
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  12. Attuning to the deep. On the opportunities of thinking with art for an ethics of the deep sea.Kristien Hens, Christina Stadlbauer & Bart Vandeput - manuscript
    Seabed mining, the extraction of minerals from the deep-sea floor, is hotly contested. Policymakers have agreed on the need for a regulatory framework. However, traditional ethical theories and principles are not well equipped for the ethics of the alien deep sea. Engaging with the sea means engaging with something abstract that we can only access indirectly. We argue that this invisibility and alienness of the sea and its inhabitants can give new insights into how ethics are done. Rather (...)
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  13. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. (...)
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  14. Deleuze and Deep Ecology.Alistair Welchman - 2008 - In Bernd Herzogenrath (ed.), An (Un)easy Alliance: Thinking the Environment with Deleuze/Guattari. pp. 116-138.
    I argue that 'deep' ecology (as exemplified by the work of Arnie Naess) involves three inter-related commitments: (1) to an ethics of nature or axiological anti-humanism in which natural entities, processes or systems can possess intrinsic value independently of human beings; (2) a metaphysical naturalism or anti-humanism in which human beings are themselves conceptualized as natural products; (3) a transformative aspect. Although (3) is sometimes cast in personal or psychological terms, I think the idea can be given a (...)
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  15. Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing (...)
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  16. Comparative Analysis of Deep Learning and Naïve Bayes for Language Processing Task.Olalere Abiodun - forthcoming - International Journal of Research and Innovation in Applied Sciences.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least (...)
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  17. General-Purpose Institutional Decision-Making Heuristics: The Case of Decision-Making under Deep Uncertainty.David Thorstad - forthcoming - British Journal for the Philosophy of Science.
    Recent work in judgment and decisionmaking has stressed that institutions, like individuals, often rely on decisionmaking heuristics. But most of the institutional decisionmaking heuristics studied to date are highly firm- and industry-specific. This contrasts to the individual case, in which many heuristics are general-purpose rules suitable for a wide range of decision problems. Are there also general-purpose heuristics for institutional decisionmaking? In this paper, I argue that a number of methods recently developed for decisionmaking under deep uncertainty have (...)
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  18. The Eight Points - A Reinterpretation of Deep Ecology.Simon Butler - manuscript
    Naess and Sessions “Deep Ecology Platform” provided a loose framework for a movement that was gaining momentum after a series of successful social and political actions and events throughout the 1970s and early 1980s. Most of the points are essentially adopted from Naess’ earlier work, which provided the basis for a number of the core concepts expressed in the later eight points and is largely an expression of a movement that sought to create a shift in consciousness of (...)
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  19. Lyotard, 'The Differend', and the Philosophy of Deep Disagreement.James Cartlidge - 2022 - Synthese 200 (359):1-19.
    This paper examines the philosophy of Jean-Francois Lyotard in relation to the analytic philosophy of deep disagreement. It argues not just that his work has relevance for this debate, but that it offers a challenge to the ‘epistemic paradigm’ present in its academic literature, represented by the two most prominent sets of theories within it – the ‘fundamental epistemic principle’ and ‘hinge epistemology’ views, arguably most strongly represented by Michael Lynch and Duncan Pritchard, respectively. Focussing on Lyotard’s text (...)
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  20. A DEEP LEARNING APPROACH FOR LSTM BASED COVID-19 FORECASTING SYSTEM.K. Jothimani - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):28-38.
    : COVID-19 has proliferated over the earth, exposing mankind at risk. The assets of the world's most powerful economies are at stake due to the disease's high infectivity and contagiousness. The capacity of machine learning algorithms can estimate the amount of future COVID-19 cases, which is now considered a possible threat to civilization. Five conventional measuring models, notably LR, LASSO, SVM, ES, and LSTM, were utilised in this work to examine COVID-19's undermining variables. Each model contains three sorts of (...)
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  21. Captioning Deep Learning Based Encoder-Decoder through Long Short-Term Memory (LSTM).Grimsby Chelsea - forthcoming - International Journal of Scientific Innovation.
    This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality (...)
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  22.  25
    Bird Species Identification Using Deep Learning.R. Senthilkumar - 2025 - Journal of Science Technology and Research (JSTAR) 6 (1):1-14.
    Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A (...)
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  23. (1 other version)Deep Learning Based Video Captioning through Encoder-Decoder Based Long Short-Term Memory (LSTM).Grimsby Chelsea - forthcoming - International Journal of Advanced Computer Science and Applications:1-6.
    This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality (...)
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  24. All my earthothers: Levinasian tools for deep ecology.Erika Natalia Molina Garcia - 2021 - In Narratives in the Anthropocene Era. Lago, Italy: Il Sileno Edizioni.
    The work of Emmanuel Levinas has been both abundantly recognized and criticized in moral philosophy. This Janus-faced attitude is also present in ecological theories, which find fertile ground in Levinas’ thought without being able to explain its apparent anthropocentrism. Opposing hermeneutical paths tend to focus either on otherness as an absolute alterity, implying a potentially unlimited responsibility for all alterities, or on otherness as a re-foundation of humanism, leading to the conclusion that responsibility is unlimited only among humans. Here (...)
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  25. Implementation and Comparison of Deep Learning with Naïve Bayes for Language Processing (4th edition).Abiodun Olalere - 2024 - Internation Journal of Research and Innovation in Appliad Science:1-6.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least (...)
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  26.  84
    Impact of Variation in Vector Space on the performance of Machine and Deep Learning Models on an Out-of-Distribution malware attack Detection.Tosin Ige - forthcoming - Ieee Conference Proceeding.
    Several state-of-the-art machine and deep learning models in the mode of adversarial training, input transformation, self adaptive training, adversarial purification, zero-shot, one- shot, and few-shot meta learning had been proposed as a possible solution to an out-of-distribution problems by applying them to wide arrays of benchmark dataset across different research domains with varying degrees of performances, but investigating their performance on previously unseen out-of- distribution malware attack remains elusive. Having evaluated the poor performances of these state-of-the-art approaches in our (...)
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  27. Deliberation across Deep Divisions. Transformative Moments.Jurg Steiner, Maria Clara Jaramillo, Rousiley C. M. Maia & Simona Mameli - 2017 - Cambridge: Cambridge University Press.
    From the local level to international politics, deliberation helps to increase mutual understanding and trust, in order to arrive at political decisions of high epistemic value and legitimacy. This book gives deliberation a dynamic dimension, analysing how levels of deliberation rise and fall in group discussions, and introducing the concept of 'deliberative transformative moments' and how they can be applied to deeply divided societies, where deliberation is most needed but also most difficult to work. Discussions between ex-guerrillas and ex-paramilitaries (...)
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  28. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is (...)
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  29. The Context of Work.David Kirsh - 2001 - Human-Computer Interaction 16:305-322.
    The question of how to conceive and represent the context of work is explored from the theoretical perspective of distributed cognition. It is argued that to understand the office work context we need to go beyond tracking superficial physical attributes such as who or what is where and when and consider the state of digital resources, people’s concepts, task state, social relations, and the local work culture, to name a few. In analyzing an office more deeply, three (...)
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  30. Mapping the Deep Blue Oceans.Rasmus Grønfeldt Winther - 2019 - In Timothy Tambassi (ed.), The Philosophy of GIS. Springer. pp. 99-123.
    The ocean terrain spanning the globe is vast and complex—far from an immense flat plain of mud. To map these depths accurately and wisely, we must understand how cartographic abstraction and generalization work both in analog cartography and digital GIS. This chapter explores abstraction practices such as selection and exaggeration with respect to mapping the oceans, showing significant continuity in such practices across cartography and contemporary GIS. The role of measurement and abstraction—as well as of political and economic power, (...)
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  31. Naming Names: A Deep Dive into Saul Kripke’s Philosophy.Nathan Salmón & Charles Carlini - 2023 - Simply Charly.
    Charles Carlini interviews Nathan Salmón about the philosophical work of his mentor and friend, the late Saul Kripke, one of the foremost philosophers of the 20th Century.
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  32. Recurrent Neural Network Based Speech emotion detection using Deep Learning.P. Pavithra - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):65-77.
    In modern days, person-computer communication systems have gradually penetrated our lives. One of the crucial technologies in person-computer communication systems, Speech Emotion Recognition (SER) technology, permits machines to correctly recognize emotions and greater understand users' intent and human-computer interlinkage. The main objective of the SER is to improve the human-machine interface. It is also used to observe a person's psychological condition by lie detectors. Automatic Speech Emotion Recognition(SER) is vital in the person-computer interface, but SER has challenges for accurate recognition. (...)
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  33. A Promethean Philosophy of External Technologies, Empiricism, & the Concept: Second-Order Cybernetics, Deep Learning, and Predictive Processing.Ekin Erkan - 2020 - Media Theory 4 (1):87-146.
    Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work (...)
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  34. Why read (diffractively)?Jean Du Toit & P. Du Preez - 2022 - South African Journal of Higher Education 36 (1):115-135.
    Academics should produce quality scholarly research. However, the demands of the marketised, neoliberal higher education institution and the increase in the academic’s bureaucratic and administrative tasks do not allow for adequate engagement with the deep work and slow forms of scholarship that are needed to produce cutting-edge and insightful research. Many academics find it challenging to think critically and creatively under such conditions, yet they are unwilling to fill their time with shallow work instead. Thus, they are (...)
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  35. Wandering in intersectional time: subjectivity and identity in Richard Flanagan’s The Narrow Road to the Deep North.Victoria Reeve - 2016 - Text 34.
    Using hokku poet Basho’s aesthetics of wandering, as defined by Thomas Heyd, I argue that, by detailing the excruciating pointlessness of work undertaken according to commands that take little or no account of their feasibility, Richard Flanagan’s novel, The Narrow Road to the Deep North (which takes its title from Basho's work) transforms the features of this aesthetics into the lived experience of prisoners of war on the ‘line’. In doing so, Flanagan transfers Basho’s aesthetics into a (...)
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  36. Plato's Work.Sfetcu Nicolae - manuscript
    Plato's entire body of work has survived intact to this day, decisively influencing Western culture. For Plato, dialogue is the only tool capable of highlighting the research character of philosophy, the key element of his thinking. Certainly the written word is more precise and in-depth than the oral one, but the oral discourse allows an immediate exchange of views on the subject under discussion. The main protagonist of the dialogues is Socrates, except for the last dialogues where he is (...)
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    Calorie Estimation of Food and Beverages using Deep Learning.R. Senthilkumar - 2025 - Journal of Science Technology and Research (JSTAR) 6 (1):1-19.
    This project aims to provide an automated system for accurately estimating the calorie content of food and beverages using advanced deep learning algorithms. With the increasing demand for health-conscious individuals, there is a need for a reliable, efficient, and easy-to-use tool that can help users make informed dietary choices. The project utilizes image processing techniques and deep learning models, such as Convolutional Neural Networks (CNN), to analyze food images and predict the corresponding calorie content. The system works by (...)
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  38. Review of Nick Bostrom's Deep Utopia. [REVIEW]Matthew Hammerton - 2024 - Notre Dame Philosophical Reviews 202411.
    Nick Bostrom is perhaps best known for his 2014 book Superintelligence, which explores the existential threat posed to humans by superintelligent AI. In his new book, Deep Utopia, he shifts gears to explore the existentialist threat that superintelligent AI poses. Suppose that humans successfully navigate the technological, moral, and political challenges that come with advanced AI. The result of such success, according to Bostrom, would be a kind of deep utopia. We would not only live in a post- (...), and post-scarcity society (things already covered by shallower conceptions of utopia); we would also live in a “post-instrumental” society where almost anything we might consider doing, including pursuing our own personal enrichment, could be better accomplished by AI. Bostrom’s central concern is how we might find meaning and purpose in such a world. If everything you might consider doing can be done better by machine intelligence, what is there to live for? (shrink)
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  39. Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5.Florentin Smarandache - 2023 - Edited by Smarandache Florentin, Dezert Jean & Tchamova Albena.
    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some (...)
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  40. Artificial Intelligence in Life Extension: from Deep Learning to Superintelligence.Alexey Turchin, Denkenberger David, Zhila Alice, Markov Sergey & Batin Mikhail - 2017 - Informatica 41:401.
    In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently (...)
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  41. Of Hatred and Solitude in the Works of Mary Shelley and E. M. Cioran.Bolea Stefan - 2017 - Philobiblon - Transilvanian Journal of Multidisciplinary Research in Humanities 22 (2):105-116.
    Despite the fact that Mary Shelley and E. M. Cioran have never been previously analyzed in the same context (they belong not only to different ages but also to divergent genres), we will find that they share at least two similar themes. The motif of solitude, common among Romantic poets (Coleridge, Byron, Poe), finds a deep expression in Shelley’s Frankenstein and in Cioran’s early oeuvre. A more thorough investigation of the British novelist and the Romanian-French self-described “anti-philosopher” discloses that (...)
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  42. The Boundaries of Meaning: A Case Study in Neural Machine Translation.Yuri Balashov - 2022 - Inquiry: An Interdisciplinary Journal of Philosophy 66.
    The success of deep learning in natural language processing raises intriguing questions about the nature of linguistic meaning and ways in which it can be processed by natural and artificial systems. One such question has to do with subword segmentation algorithms widely employed in language modeling, machine translation, and other tasks since 2016. These algorithms often cut words into semantically opaque pieces, such as ‘period’, ‘on’, ‘t’, and ‘ist’ in ‘period|on|t|ist’. The system then represents the resulting segments in a (...)
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  43. Tradizioni religiose e diversità.Daniele Bertini - 2016 - Verona: Edizioni Fondazione Centro Studi Campostrini.
    Most literature on religious beliefs and disagreements among traditions focuses on a bit of mainstream assumptions: religions should be construed in substantive terms; religions are to be individuated by their core belief systems; adherents to a single tradition assent to the same belief system; religious beliefs have factual content; incompatible religious beliefs cannot be both true; and so on. In my work I question all these claims in order to defend a non kantian approach to deep pluralism. In (...)
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  44. Operationalising Representation in Natural Language Processing.Jacqueline Harding - 2023 - British Journal for the Philosophy of Science.
    Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular (...)
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  45. Thomas White on Location and the Ontological Status of Accidents.Han Thomas Adriaenssen - 2021 - Oxford Studies in Early Modern Philosophy 10:1-35.
    The work of Thomas White represents a systematic attempt to combine the best of the new science of the seventeenth century with the best of Aristotelian tradition. This attempt earned him the criticism of Hobbes and the praise of Leibniz, but today, most of his attempts to navigate between traditions remain to be explored in detail. This paper does so for his ontology of accidents. It argues that his criticism of accidents in the category of location as entities over (...)
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  46. The many encounters of Thomas Kuhn and French epistemology.Simons Massimiliano - 2017 - Studies in History and Philosophy of Science Part A 61:41-50.
    The work of Thomas Kuhn has been very influential in Anglo-American philosophy of science and it is claimed that it has initiated the historical turn. Although this might be the case for English speaking countries, in France an historical approach has always been the rule. This article aims to investigate the similarities and differences between Kuhn and French philosophy of science or ‘French epistemology’. The first part will argue that he is influenced by French epistemologists, but by lesser known (...)
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  47. Performance vs. competence in human–machine comparisons.Chaz Firestone - 2020 - Proceedings of the National Academy of Sciences 41.
    Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when such (...)
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  48. Reconnecting with Nature in the Age of Technology.Vincent Blok - 2014 - Environmental Philosophy 11 (2):307-332.
    The relation between Martin Heidegger and radical environmentalism has been subject of discussion for several years now. On the one hand, Heidegger is portrayed as a forerunner of the deep ecology movement, providing an alternative for the technological age we live in. On the other, commentators contend that the basic thrust of Heidegger’s thought cannot be found in such an ecological ethos. In this article, this debate is revisited in order to answer the question whether it is possible to (...)
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  49. Logical Disagreement.Frederik J. Andersen - 2024 - Dissertation, University of St. Andrews
    While the epistemic significance of disagreement has been a popular topic in epistemology for at least a decade, little attention has been paid to logical disagreement. This monograph is meant as a remedy. The text starts with an extensive literature review of the epistemology of (peer) disagreement and sets the stage for an epistemological study of logical disagreement. The guiding thread for the rest of the work is then three distinct readings of the ambiguous term ‘logical disagreement’. Chapters 1 (...)
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  50. Blame mitigation: A less tidy take and its philosophical implications.Jennifer L. Daigle & Joanna Demaree-Cotton - 2022 - Philosophical Psychology 35 (4):490-521.
    Why do we find agents less blameworthy when they face mitigating circumstances, and what does this show about philosophical theories of moral responsibility? We present novel evidence that the tendency to mitigate the blameworthiness of agents is driven both by the perception that they are less normatively competent—in particular, less able to know that what they are doing is wrong—and by the perception that their behavior is less attributable to their deep selves. Consequently, we argue that philosophers cannot rely (...)
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