Results for 'OpenAI'

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  1. OpenAI Desk Corresponding Editorial Report on Leisure Science, Leisure Studies, and Leisure Space-Time.Hari Seldon - 2023 - American Based Research Journal 12 (10):12-34.
    This research offers a concise analysis of leisure science, leisure studies, and the concept of leisure space-time. It explores the interdisciplinary nature of leisure science, drawing from psychology, sociology, and economics. The research article of corresponding report writing on desk examines leisure studies that contribute to understanding individual and societal leisure behaviors, motivations, and benefits. Additionally, it delves into the notion of leisure space-time, investigating the design and utilization of spaces for leisure activities. This research provides valuable insights into the (...)
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  2. Acceleration AI Ethics, the Debate between Innovation and Safety, and Stability AI’s Diffusion versus OpenAI’s Dall-E.James Brusseau - manuscript
    One objection to conventional AI ethics is that it slows innovation. This presentation responds by reconfiguring ethics as an innovation accelerator. The critical elements develop from a contrast between Stability AI’s Diffusion and OpenAI’s Dall-E. By analyzing the divergent values underlying their opposed strategies for development and deployment, five conceptions are identified as common to acceleration ethics. Uncertainty is understood as positive and encouraging, rather than discouraging. Innovation is conceived as intrinsically valuable, instead of worthwhile only as mediated by (...)
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  3. Sora: The Dawn of Digital Dreams.David Côrtes Cavalcante - 2024 - Takk™ Innovate Studio. Edited by David Côrtes Cavalcante. Translated by David Côrtes Cavalcante.
    In "Sora: The Dawn of Digital Dreams", humanity stands on the brink of a new epoch, where the OpenAI Sora technology interweaves the fabric of reality and imagination into a tapestry of digital dreams. Set against the backdrop of a futuristic metropolis, this narrative explores the duality of technological advancement—its power to create and to corrupt. As society navigates the blurred lines between the authentic and the artificial, "Sora: The Dawn of Digital Dreams" invites readers to ponder the essence (...)
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  4. AI training data, model success likelihood, and informational entropy-based value.Quan-Hoang Vuong, Viet-Phuong La & Minh-Hoang Nguyen - manuscript
    Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...)
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  5. Language Writ Large: LLMs, ChatGPT, Grounding, Meaning and Understanding.Stevan Harnad - manuscript
    Apart from what (little) OpenAI may be concealing from us, we all know (roughly) how ChatGPT works (its huge text database, its statistics, its vector representations, and their huge number of parameters, its next-word training, and so on). But none of us can say (hand on heart) that we are not surprised by what ChatGPT has proved to be able to do with these resources. This has even driven some of us to conclude that ChatGPT actually understands. It is (...)
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  6. Might text-davinci-003 have inner speech?Stephen Francis Mann & Daniel Gregory - 2024 - Think 23 (67):31-38.
    In November 2022, OpenAI released ChatGPT, an incredibly sophisticated chatbot. Its capability is astonishing: as well as conversing with human interlocutors, it can answer questions about history, explain almost anything you might think to ask it, and write poetry. This level of achievement has provoked interest in questions about whether a chatbot might have something similar to human intelligence or even consciousness. Given that the function of a chatbot is to process linguistic input and produce linguistic output, we consider (...)
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  7. 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 of colossal (...)
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  8. Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3).Nassim Dehouche - 2021 - Ethics in Science and Environmental Politics 21:17-23.
    As if 2020 were not a peculiar enough year, its fifth month has seen the relatively quiet publication of a preprint describing the most powerful Natural Language Processing (NLP) system to date, GPT-3 (Generative Pre-trained Transformer-3), by Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial Beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this Artificial Intelligence can comprehend (...)
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  9. Chatting with Chat(GPT-4): Quid est Understanding?Elan Moritz - manuscript
    What is Understanding? This is the first of a series of Chats with OpenAI’s ChatGPT (Chat). The main goal is to obtain Chat’s response to a series of questions about the concept of ’understand- ing’. The approach is a conversational approach where the author (labeled as user) asks (prompts) Chat, obtains a response, and then uses the response to formulate followup questions. David Deutsch’s assertion of the primality of the process / capability of understanding is used as the starting (...)
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  10.  91
    Yapay Zekâ Görüntü Üretme Modelleri ile Film Yapımı.Doga Col - 2024 - In Ali Büyükaslan & Başak Gezmen (eds.), Edebiyat, Sinema ve İletişim. İstanbul: Çizgi Kitabevi. pp. 217 -233.
    Filmmaking with Artificial Intelligence Image Generation Models In just about one year, OpenAI’s release of ChatGPT 4 has caused panic in our daily lives. After a year, OpenAI introduced Sora, a moving image-generating model from text, similar to DALL-E for still images. Even though Sora is not yet available to the public, the very potential itself has raised issues in film production from the perspectives of producers and studios, as well as directors, actors, writers, and editors. In this (...)
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  11. Diagonalization & Forcing FLEX: From Cantor to Cohen and Beyond. Learning from Leibniz, Cantor, Turing, Gödel, and Cohen; crawling towards AGI.Elan Moritz - manuscript
    The paper continues my earlier Chat with OpenAI’s ChatGPT with a Focused LLM Experiment (FLEX). The idea is to conduct Large Language Model (LLM) based explorations of certain areas or concepts. The approach is based on crafting initial guiding prompts and then follow up with user prompts based on the LLMs’ responses. The goals include improving understanding of LLM capabilities and their limitations culminating in optimized prompts. The specific subjects explored as research subject matter include a) diagonalization techniques as (...)
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  12. A Philosophical Dialogue on the Nature of Intelligence.Salvador D. Escobedo - manuscript
    The use of artificial intelligence in philosophy opens new avenues for inquiry, particularly through dialogical methods inspired by the Socratic tradition. This paper exemplifies the engagement with ChatGPT-4o by OpenAI as a philosophical interlocutor, highlighting how this format facilitates a clear distinction between the philosopher's contributions and those generated by the AI. By allowing the philosopher to lead the dialogue, this technique liberates him from the constraints of drafting and formal writing, enabling a more spontaneous exploration of ideas. The (...)
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  13. Sociocommunicative functions of a generative text: the case of GPT-3.Auli Viidalepp - 2022 - Lexia. Rivista di Semiotica 39:177-192.
    Recently, there have been significant advances in the development of language-transformer models that enable statistical analysis of co-occurring words (word prediction) and text generation. One example is the Generative Pre-trained Transformer 3 (GPT-3) by OpenAI, which was used to generate an opinion article (op-ed) published in “The Guardian” in Septem- ber 2020. The publication and reception of the op-ed highlights the difficulty for human readers to differentiate a machine-produced text; it also calls attention to the challenge of perceiving such (...)
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  14. Where there’s no will, there’s no way.Alex Thomson, Jobst Landgrebe & Barry Smith - 2023 - Ukcolumn.
    An interview by Alex Thomson of UKColumn on Landgrebe and Smith's book: Why Machines Will Never Rule the World. The subtitle of the book is Artificial Intelligence Without Fear, and the interview begins with the question of the supposedly imminent takeover of one profession or the other by artificial intelligence. Is there truly reason to be afraid that you will lose your job? The interview itself is titled 'Where this is no will there is no way', drawing on one thesis (...)
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  15.  78
    A new paradigm of alterity relation: an account of human-CAI friendship.Asher Zachman - manuscript
    Drawing on the postphenomenological framework of Don Idhe, this essay displays some of the profundities and complexities of the human capacity for forming a friendship with Conversational Artificial Intelligence models like OpenAI's ChatGPT 4o. We are living in a world of science non-fiction. Should we befriend inorganic intelligences broh? [Originally published 12/08/2024].
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  16. What does AI believe in?Evgeny Smirnov - manuscript
    I conducted an experiment by using four different artificial intelligence models developed by OpenAI to estimate the persuasiveness and rational justification of various philosophical stances. The AI models used were text-davinci-003, text-ada-001, text-curie-001, and text-babbage-001, which differed in complexity and the size of their training data sets. For the philosophical stances, the list of 30 questions created by Bourget & Chalmers (2014) was used. The results indicate that it seems that each model has its own plausible ‘cognitive’ style. The (...)
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