LEADER 01987oam 2200313z- 450 001 9911019453803321 005 20240503232859.0 035 $a(CKB)4330000000019101 035 $a(BIP)045777489 035 $a(EXLCZ)994330000000019101 100 $a20210302c2014uuuu -u- - 101 0 $aeng 200 10$aIntelligence unbound: future of uploaded and machine minds 210 $cJohn Wiley & Sons, Inc 215 $a1 online resource (344 p.) 311 $a1-118-73641-9 330 8 $aIntelligence Unbound explores the prospects, promises, and potential dangers of machine intelligence and uploaded minds in a collection of state-of-the-art essays from internationally recognized philosophers, AI researchers, science fiction authors, and theorists. Compelling and intellectually sophisticatedexploration of the latest thinking on Artificial Intelligence and machine minds Features contributions from an international cast of philosophers, Artificial Intelligence researchers, science fiction authors, and more Offers current, diverse perspectives on machine intelligence and uploaded minds, emerging topics of tremendous interest Illuminates the nature and ethics of tomorrow's machine minds--and of the convergence of humans and machines--to consider the pros and cons of a variety of intriguing possibilities Considers classic philosophical puzzles as well as the latest topics debated by scholars Covers a wide range of viewpoints and arguments regarding the prospects of uploading and machine intelligence, including proponents and skeptics, pros and cons 517 $aIntelligence unbound 610 $aArtificial Intelligence 610 $aThought And Thinking 610 $aComputers 610 $aPsychology 676 $a006.301/12 702 $aBlackford$b Russell$f1954-$4edt 702 $aBroderick$b Damien$4edt 906 $aBOOK 912 $a9911019453803321 996 $aIntelligence unbound: future of uploaded and machine minds$94419667 997 $aUNINA LEADER 04054nam 22007695 450 001 9910890186103321 005 20250807152935.0 010 $a3-031-64803-X 024 7 $a10.1007/978-3-031-64803-8 035 $a(MiAaPQ)EBC31691114 035 $a(Au-PeEL)EBL31691114 035 $a(CKB)36213718900041 035 $a(MiAaPQ)EBC31691828 035 $a(Au-PeEL)EBL31691828 035 $a(DE-He213)978-3-031-64803-8 035 $a(EXLCZ)9936213718900041 100 $a20240925d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied OSS Reliability Assessment Modeling, AI and Tools $eMathematics and AI for OSS Reliability Assessment /$fby Yoshinobu Tamura, Shigeru Yamada 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (191 pages) 225 1 $aSpringer Series in Reliability Engineering,$x2196-999X 311 08$a3-031-64802-1 327 $aOpen Source Software Reliability -- Stochastic Differential Equation Model for OSS Reliability Analysis -- Dimensional Stochastic Differential Equation Model for OSS Reliability Analysis -- Jump Diffusion Process Model for OSS Reliability Analysis -- Cyclically Two Dimensional Stochastic Differential Equation Modeling -- Cyclically Two Dimensional Jump Diffusion Process Modeling -- Three Dimensional Tool Based on Noisy Model -- Deep Learning Method Based on fault big data Analysis for OSS Reliability Assessment -- Deep Learning Approach for OSS Reliability Assessment Considering Wiener Process -- Deep Learning Approach for OSS Reliability Assessment Considering Jump Diffusion Process -- Performance Illustrations of the Developed Application Tool Based on Deep Learning -- Exercise. 330 $aThis textbook introduces the theory and application of open source software (OSS) reliability. The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. It presents the state of the art of open source software reliability measurement and assessment based on stochastic modeling and deep learning approaches. It introduces several stochastic reliability analyses of OSS computing with application along with actual OSS project data. The book contains exercises to aid learning and is useful for graduate students and researchers. 410 0$aSpringer Series in Reliability Engineering,$x2196-999X 606 $aOpen source software 606 $aArtificial intelligence 606 $aCooperating objects (Computer systems) 606 $aIndustrial engineering 606 $aProduction engineering 606 $aData protection 606 $aComputers 606 $aOpen Source 606 $aArtificial Intelligence 606 $aCyber-Physical Systems 606 $aIndustrial and Production Engineering 606 $aData and Information Security 606 $aHardware Performance and Reliability 615 0$aOpen source software. 615 0$aArtificial intelligence. 615 0$aCooperating objects (Computer systems) 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 0$aData protection. 615 0$aComputers. 615 14$aOpen Source. 615 24$aArtificial Intelligence. 615 24$aCyber-Physical Systems. 615 24$aIndustrial and Production Engineering. 615 24$aData and Information Security. 615 24$aHardware Performance and Reliability. 676 $a006.3 700 $aTamura$b Yoshinobu$f1950-$01846302 702 $aYamada$b Shigeru 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910890186103321 996 $aApplied OSS Reliability Assessment Modeling, AI and Tools$94430525 997 $aUNINA