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UNIVERSAL SCIENCE OF MIND: CAN COMPLEXITY-BASED ARTIFICIAL INTELLIGENCE SAVE THE WORLD IN CRISIS?
Andrei P. Kirilyuk

UNIVERSAL SCIENCE OF MIND: CAN COMPLEXITY-BASED ARTIFICIAL INTELLIGENCE SAVE THE WORLD IN CRISIS?

Author / Organization:
Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

While practical efforts in the field of artificial intelligence grow exponentially, the truly scientific and mathematically exact understanding of the underlying phenomena of intelligence and consciousness is still missing in the conventional science framework. The inevitably dominating empirical, trial-and-error approach has vanishing efficiency for those extremely complicated phenomena, ending up in fundamentally limited imitations of intelligent behaviour. We provide the first-principle analysis of unreduced many-body interaction process in the brain revealing its qualitatively new features, which give rise to rigorously defined chaotic, noncomputable, intelligent and conscious behaviour. Based on the obtained universal concepts of unreduced dynamic complexity, intelligence and consciousness, we derive the universal laws of intelligence applicable to any kind of intelligent system interacting with the environment. We finally show why and how these fundamentally substantiated and therefore practically efficient laws of intelligent system dynamics are indispensable for correct AI design and training, which is urgently needed in this time of critical global change towards the truly sustainable development.

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Document Information

Document Title UNIVERSAL SCIENCE OF MIND: CAN COMPLEXITY-BASED ARTIFICIAL INTELLIGENCE SAVE THE WORLD IN CRISIS?
Author / Organization Andrei P. Kirilyuk
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-149898
Original Source Link Visit Source Page on hal.science »