{"title":"利用人工智能系统对大脑复杂器官--有机体进行研究,以进化大脑的主要特征--表现形式(自组织)","authors":"V. R. Raju","doi":"10.18231/j.ijn.2023.043","DOIUrl":null,"url":null,"abstract":": Embedding carnal (somatic or physical) restraints over the artificial intelligent system (i.e., artificially-intelligent system) in ample the similar way that the ‘human-brain’ must grow, progress plus function in the physically real, tangible and biological constrictions that lets system to advance feature-manifestations of the brains of multifaceted organs and organisms so as to solve brain issues. : Placing carnal restraints on AI-based model-system, i.e., artificially intelligent system. : spatially embedded recurrent neural nets (RNNs), 3D Euclidean space, where message of fundamental neural-cells are hampered by ‘sparse-connectome’ recurrent-neural-nets (RNN). : RNNs converge over anatomical, structural functional features universally originate within primates (cardinal, mandrill), and macaques’ cerebral/rational, brainy-cortices. Explicitly, they congregate/ (converge) over resolving implications via segmental (modular) tiny-world nets, in which functionally analogous-units spatially configure/construct themselves to use the dynamically effective varied-discerning code. Since features occur in union RNNs show how many mutual anatomical, functional-brain patterns (motifs) are deeply linked, can be ascribed to basic biologic optimization-processes. : RNNs merge biophysical limits in AI system plus aid as a bridge amid anatomical functional researchers to move ability neuroscience on.","PeriodicalId":415114,"journal":{"name":"IP Indian Journal of Neurosciences","volume":"435 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A study of brains complex organs-organisms with artificial intelligence system to evolve cardinal feature-manifestations of brain`s (self-organizing)\",\"authors\":\"V. R. Raju\",\"doi\":\"10.18231/j.ijn.2023.043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Embedding carnal (somatic or physical) restraints over the artificial intelligent system (i.e., artificially-intelligent system) in ample the similar way that the ‘human-brain’ must grow, progress plus function in the physically real, tangible and biological constrictions that lets system to advance feature-manifestations of the brains of multifaceted organs and organisms so as to solve brain issues. : Placing carnal restraints on AI-based model-system, i.e., artificially intelligent system. : spatially embedded recurrent neural nets (RNNs), 3D Euclidean space, where message of fundamental neural-cells are hampered by ‘sparse-connectome’ recurrent-neural-nets (RNN). : RNNs converge over anatomical, structural functional features universally originate within primates (cardinal, mandrill), and macaques’ cerebral/rational, brainy-cortices. Explicitly, they congregate/ (converge) over resolving implications via segmental (modular) tiny-world nets, in which functionally analogous-units spatially configure/construct themselves to use the dynamically effective varied-discerning code. Since features occur in union RNNs show how many mutual anatomical, functional-brain patterns (motifs) are deeply linked, can be ascribed to basic biologic optimization-processes. : RNNs merge biophysical limits in AI system plus aid as a bridge amid anatomical functional researchers to move ability neuroscience on.\",\"PeriodicalId\":415114,\"journal\":{\"name\":\"IP Indian Journal of Neurosciences\",\"volume\":\"435 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IP Indian Journal of Neurosciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18231/j.ijn.2023.043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IP Indian Journal of Neurosciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18231/j.ijn.2023.043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study of brains complex organs-organisms with artificial intelligence system to evolve cardinal feature-manifestations of brain`s (self-organizing)
: Embedding carnal (somatic or physical) restraints over the artificial intelligent system (i.e., artificially-intelligent system) in ample the similar way that the ‘human-brain’ must grow, progress plus function in the physically real, tangible and biological constrictions that lets system to advance feature-manifestations of the brains of multifaceted organs and organisms so as to solve brain issues. : Placing carnal restraints on AI-based model-system, i.e., artificially intelligent system. : spatially embedded recurrent neural nets (RNNs), 3D Euclidean space, where message of fundamental neural-cells are hampered by ‘sparse-connectome’ recurrent-neural-nets (RNN). : RNNs converge over anatomical, structural functional features universally originate within primates (cardinal, mandrill), and macaques’ cerebral/rational, brainy-cortices. Explicitly, they congregate/ (converge) over resolving implications via segmental (modular) tiny-world nets, in which functionally analogous-units spatially configure/construct themselves to use the dynamically effective varied-discerning code. Since features occur in union RNNs show how many mutual anatomical, functional-brain patterns (motifs) are deeply linked, can be ascribed to basic biologic optimization-processes. : RNNs merge biophysical limits in AI system plus aid as a bridge amid anatomical functional researchers to move ability neuroscience on.