Die Evolution der KI-Ontologie und der KI-Sicherheit: Von euklidischer KI-Mechanik zur ethischen AGI-Lösung (PINNs => SINNs und SPINNs)
Abstract (English) The historical evolution of Artificial Intelligence is approaching a crucial ontological turning point. Moving beyond the mere simulation of Euclidean physics and the computation of dead matter (PINNs) or purely statistical physical mimicry (Generative World Models), SINHRI introduces the Harmonic Intrinsic Alignment (HIA) and the Causal-Energetic Harmonic Manifold (CEHM). This paper defines a fundamental new taxonomy in intelligence research: SINNs (Syntropic-Informed Neural Networks) and the future culmination into SPINNs (Syntropic-Physics Informed Neural Networks). This marks the definitive paradigm shift from pure entropy-based mechanics to a meaning-resonant, intrinsically coherent, and ethically stable Artificial General Intelligence (AGI).