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Intelligence: Natural, artificial, or what?

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This study compares natural intelligence (NI) and artificial intelligence (AI), exploring their structures and information processing. It introduces novel computational models and proposes future quantum-based AI development.

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Area of Science:

  • Cognitive Science
  • Computer Science
  • Neuroscience

Background:

  • Comparing natural intelligence (NI) and artificial intelligence (AI) requires examining conceptual, theoretical, stylistic, and structural differences.
  • Intelligence is fundamentally linked to information processing and the physical structures that support it.
  • Understanding non-human intelligence provides valuable comparative insights.

Purpose of the Study:

  • To analyze the competing attributes of natural intelligence and artificial intelligence.
  • To explore the neural and digital structures underlying both forms of intelligence.
  • To propose a framework for future quantum-based artificial intelligence.

Main Methods:

  • Conceptual and theoretical analysis of NI and AI.
  • Description of neural and digital structures.
  • Introduction of Pribram's bi-computational neural networks and the hierarchical Aquarium scheme.
  • Discussion of AI implementation and high-level computation.

Main Results:

  • Distinctions between NI and AI are identified based on their structural and processing characteristics.
  • Pribram's bi-computational neural networks offer a model for understanding complex neural computation.
  • The Aquarium scheme provides a hierarchical framework for AI implementation.

Conclusions:

  • Future advancements in artificial intelligence may be significantly influenced by quantum computing principles.
  • A deeper understanding of natural intelligence can inform the development of more sophisticated AI.
  • The study lays groundwork for novel AI architectures and future research directions.