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Status of the Evaluation of the Cosmological Inquiry “What Is It All About?”
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作者 M.Radh Achuthan 《Journal of Philosophy Study》 2021年第5期379-382,共4页
In general,members of all different cultures are concerned about the cosmological query“What it is all about”.In the literature,many commentaries are available to us on the question.Nevertheless,a comprehensive,brie... In general,members of all different cultures are concerned about the cosmological query“What it is all about”.In the literature,many commentaries are available to us on the question.Nevertheless,a comprehensive,brief summary,as below,of the state of this inquiry on the subject may be helpful. 展开更多
关键词 BRAHMAN Maya process reality ONI^(1)kin altruism reciprocal altruism empathetic altruism SAI(strong artificial intelligence)
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Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?
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作者 Danko Nikolic 《International Journal of Automation and computing》 EI CSCD 2017年第5期532-541,共10页
The recently introduced theory of practopoiesis offers an account on how adaptive intelligent systems are organized. According to that theory, biological agents adapt at three levels of organization and this structure... The recently introduced theory of practopoiesis offers an account on how adaptive intelligent systems are organized. According to that theory, biological agents adapt at three levels of organization and this structure applies also to our brains. This is referred to as tri-traversal theory of the organization of mind or for short, a T3-structure. To implement a similar T3-organization in an artificially intelligent agent, it is necessary to have multiple policies, as usually used as a concept in the theory of reinforcement learning. These policies have to form a hierarchy. We define adaptive practopoietic systems in terms of hierarchy of policies and calculate whether the total variety of behavior required by real-life conditions of an adult human can be satisfactorily accounted for by a traditional approach to artificial intelligence based on T2-agents, or whether a T3-agent is needed instead. We conclude that the complexity of real life can be dealt with appropriately only by a T3-agent. This means that the current approaches to artifidal intelligence, such as deep architectures of neural networks, will not suffice with fixed network architectures. Rather, they will need to be equipped with intelligent mechanisms that rapidly alter the architectures of those networks. 展开更多
关键词 Artificial intelligence neural networks strong artificial intelligence practopoiesis machine learning
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Does Wittgenstein Actually Undermine the Foundation of Artificial Intelligence?
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作者 XU Yingjin 《Frontiers of Philosophy in China》 2016年第1期3-20,共18页
Wittgenstein is widely viewed as a potential critic of a key philosophical assumption of the Strong Artificial Intelligence (AI) thesis, namely, that it is in principle possible to build a programmed machine which c... Wittgenstein is widely viewed as a potential critic of a key philosophical assumption of the Strong Artificial Intelligence (AI) thesis, namely, that it is in principle possible to build a programmed machine which can achieve real intelligence. Smart Shanker has provided the most systematic reconstruction of the Wittgensteinian argument against AI, building on Wittgenstein's own statements, the "rule-following" feature of language-games, and the putative alliance between AI and psychologism. This article will attempt to refute this reconstruction and its constituent arguments, thereby paving the way for a new and amicable rather than agonistic conception of the Wittgensteinian position on AI. 展开更多
关键词 strong Artificial intelligence (AI) rule-following psychologism algorithm
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AIGC challenges and opportunities related to public safety:A case study of ChatGPT 被引量:3
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作者 Danhuai Guo Huixuan Chen +1 位作者 Ruoling Wu Yangang Wang 《Journal of Safety Science and Resilience》 EI CSCD 2023年第4期329-339,共11页
Artificial intelligence generated content(AIGC)is a production method based on artificial intelligence(AI)technology that finds rules through data and automatically generates content.In contrast to computational intel... Artificial intelligence generated content(AIGC)is a production method based on artificial intelligence(AI)technology that finds rules through data and automatically generates content.In contrast to computational intelligence,generative AI,as exemplified by ChatGPT,exhibits characteristics that increasingly resemble human-level comprehension and creation processes.This paper provides a detailed technical framework and history of ChatGPT,followed by an examination of the challenges posed to political security,military security,economic security,cultural security,social security,ethical security,legal security,machine escape problems,and information leakage.Finally,this paper discusses the potential opportunities that AIGC presents in the realms of politics,military,cybersecurity,society,and public safety education. 展开更多
关键词 Generative artificial intelligence Artificial intelligence generated content ChatGPT Public safety strong artificial intelligence
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