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Is coding a relevant metaphor for building AI?

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The neural coding metaphor is insufficient for understanding brain function and building artificial intelligence. It fails to guide AI in achieving goals within complex, dynamic environments.

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Cognitive Science

Background:

  • The neural coding metaphor posits that brain function can be understood by deciphering neural activity patterns.
  • This metaphor has been a foundational concept in neuroscience and artificial intelligence research.
  • However, its limitations in explaining complex brain processes are increasingly recognized.

Purpose of the Study:

  • To critically evaluate the adequacy of the neural coding metaphor as a basis for AI.
  • To demonstrate why this metaphor is insufficient for developing artificial intelligence capable of goal-directed learning in complex environments.

Main Methods:

  • Conceptual analysis of the neural coding metaphor.
  • Argumentation based on the requirements for artificial intelligence systems operating in dynamic environments.

Main Results:

  • The neural coding metaphor is deemed an invalid basis for theories of brain function.
  • It is insufficient for guiding the development of artificial intelligence that learns to achieve goals in complex, changing environments.

Conclusions:

  • Rethinking the foundational metaphors in neuroscience is crucial.
  • New theoretical frameworks are needed for advancing artificial intelligence beyond current limitations.