[The concept of intuitive and logical in neurocomputing]

Area of Science:

• Neuroscience
• Computer Science
• Artificial Intelligence

Background:

• Modern neural computing faces challenges in simulating complex cognitive functions.
• Existing models struggle to replicate human intuition, creativity, and other nuanced behaviors.

Purpose of the Study:

• To propose a new neural computer architecture.
• To address limitations in current artificial intelligence by incorporating complementary subsystems for learning and information storage.
• To explore the simulation of human-specific cognitive effects in artificial intellect.

Main Methods:

• Conceptualizing a dual-subsystem architecture for neural computers.
• Integrating a "noise" element into the learning subsystem.
• Discussing methods for simulating human-like effects such as humor and sleep.

Main Results:

• A novel neural computer arrangement is proposed.
• The concept suggests complementary roles for knowledge acquisition and information storage subsystems.
• The learning subsystem is designed to include an "occasional element" or "noise".

Conclusions:

• The proposed architecture offers a potential solution for specific neural computing challenges.
• This approach may enable artificial intelligence to exhibit effects like intuition and creativity.
• Further methods are suggested for simulating a wider range of human cognitive phenomena in AI.