Comparing Neural Networks In Human Brains And AI Systems With Focus On Genetics And Experiential Differences

This research investigates the comparative dynamics between human intelligence and artificial intelligence (AI), focusing on the parallels between the human brain and microprocessors. It begins by exploring the foundational principles of cognition and computing, emphasizing how microprocessors have drawn inspiration from the brain's complexity. Despite their distinct compositions, both the human brain and microprocessors exhibit similarities in information processing, storage, and execution, mirroring each other’s mechanisms through electrical impulses and interconnected components. The study reviews literature on AI working, the influence of genetics and environmental factors on human behavior, and the capabilities of neural networks. The research underscores the significance of genetic inheritance, its effect on neural networks in humans along with the environmental experiences in shaping behavior and personality. The findings contribute to a deeper understanding of both biological and artificial intelligence. Ultimately, this study demonstrates the potential for leveraging insights from both domains to enhance human well-being and technological progress.