the Observer Centric Universe, Quantum Mechanics and Path to AGI Alignment

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Bol This book explores the profound challenge of artificial general intelligence (AGI) alignment, arguing that an algorithmic approach to creating conscious and empathic AI is fundamentally limited. Building on the author’s N-Frame model, it extends this critique to the P ? NP problem, proposing that consciousness reflects a non-computable process beyond formal algorithmic closure. Drawing on philosophy, cognitive science, physics, mathematics, and evolutionary theory, the book introduces a quantum-mechanical AdS/CFT-inspired framework linking thermodynamic models of the observer with functional contextualism and evolution. It argues that solving AGI alignment requires recognising the intrinsic boundary between computation and cognition. The book concludes by exploring how truly conscious AI could promote prosocial behaviour, morality, empathy, and trust, fostering social cohesion and redefining intelligence and consciousness itself.

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This book explores the profound challenge of artificial general intelligence (AGI) alignment, arguing that an algorithmic approach to creating conscious and empathic AI is fundamentally limited. Building on the author’s N-Frame model, it extends this critique to the P ? NP problem, proposing that consciousness reflects a non-computable process beyond formal algorithmic closure. Drawing on philosophy, cognitive science, physics, mathematics, and evolutionary theory, the book introduces a quantum-mechanical AdS/CFT-inspired framework linking thermodynamic models of the observer with functional contextualism and evolution. It argues that solving AGI alignment requires recognising the intrinsic boundary between computation and cognition. The book concludes by exploring how truly conscious AI could promote prosocial behaviour, morality, empathy, and trust, fostering social cohesion and redefining intelligence and consciousness itself.

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Pagina's: 400, Hardcover, Palgrave Macmillan


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Merk Macmillan
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  • 9783032156273
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