This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and ...This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and AI researchers regarding ChatGPT’s ability to pass the Turing Test. It introduces a hierarchical categorization of the test versions, suggesting that ChatGPT approaches success in the test, albeit primarily with na?ve users. Expert users, conversely, can easily identify its limitations. The paper presents various theories of consciousness, with a particular focus on the Integrated Information Theory proposed by Tononi. This theory serves as the framework for assessing ChatGPT’s level of consciousness. Through an evaluation based on the five axioms and theorems of IIT, the study finds that ChatGPT surpasses previous AI systems in certain aspects;however, ChatGPT significantly falls short of achieving a level of consciousness, particularly when compared to biological sentient beings. The paper concludes by emphasizing the importance of recognizing ChatGPT and similar generative AI models as highly advanced and intelligent tools, yet distinctly lacking the consciousness attributes found in advanced living organisms.展开更多
In this paper it is envisaged that cognitive radios (CRs) consult a supporting network infrastructure for per-mission to transmit. The network server either grants or rejects these requests by estimating, from the CR...In this paper it is envisaged that cognitive radios (CRs) consult a supporting network infrastructure for per-mission to transmit. The network server either grants or rejects these requests by estimating, from the CR’s geo-location and antenna features, the likely impact its transmission would have on incumbents and other CR devices. This decision would be based on a real-time radio environment map [1] which would be kept up to date with readings from CRs, sensors and dynamic radio propagation prediction. By this means coexistence with incumbents and other CRs can be satisfied. It is maintained here that integral-equation (IE) - based al-gorithms are suitable candidates for the propagation engine given their ‘automatic’ nature and that they can be implemented to give results arbitrarily close to the exact numerical solution. IE methods based on the Fast Multipole Method are examined as a likely route to achieve the accuracy and speed necessary for real-time propagation mapping. It is concluded that the results obtained using one of the most recent of these, the Field Extrapolation Method (FEXM) [2], are promising for rural/suburban profiles and could serve to enable co-existence, for example, in IEEE802.22 networks. It is also explained how dynamic propagation prediction can address some fundamental security threats to CR networks.展开更多
文摘This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and AI researchers regarding ChatGPT’s ability to pass the Turing Test. It introduces a hierarchical categorization of the test versions, suggesting that ChatGPT approaches success in the test, albeit primarily with na?ve users. Expert users, conversely, can easily identify its limitations. The paper presents various theories of consciousness, with a particular focus on the Integrated Information Theory proposed by Tononi. This theory serves as the framework for assessing ChatGPT’s level of consciousness. Through an evaluation based on the five axioms and theorems of IIT, the study finds that ChatGPT surpasses previous AI systems in certain aspects;however, ChatGPT significantly falls short of achieving a level of consciousness, particularly when compared to biological sentient beings. The paper concludes by emphasizing the importance of recognizing ChatGPT and similar generative AI models as highly advanced and intelligent tools, yet distinctly lacking the consciousness attributes found in advanced living organisms.
文摘In this paper it is envisaged that cognitive radios (CRs) consult a supporting network infrastructure for per-mission to transmit. The network server either grants or rejects these requests by estimating, from the CR’s geo-location and antenna features, the likely impact its transmission would have on incumbents and other CR devices. This decision would be based on a real-time radio environment map [1] which would be kept up to date with readings from CRs, sensors and dynamic radio propagation prediction. By this means coexistence with incumbents and other CRs can be satisfied. It is maintained here that integral-equation (IE) - based al-gorithms are suitable candidates for the propagation engine given their ‘automatic’ nature and that they can be implemented to give results arbitrarily close to the exact numerical solution. IE methods based on the Fast Multipole Method are examined as a likely route to achieve the accuracy and speed necessary for real-time propagation mapping. It is concluded that the results obtained using one of the most recent of these, the Field Extrapolation Method (FEXM) [2], are promising for rural/suburban profiles and could serve to enable co-existence, for example, in IEEE802.22 networks. It is also explained how dynamic propagation prediction can address some fundamental security threats to CR networks.
