Neural Odyssey: Charting the Unseen Depths of Artificial Intelligence Cognition

Abstract

Artificial Intelligence (AI) has evolved from simple rule-based systems to complex deep learning architectures capable of human-like cognitive processes. This paper explores the unseen depths of AI cognition, delving into neural networks, self-learning algorithms, and the enigmatic black-box nature of deep learning models. We examine how AI mimics human cognition, its limitations, and the quest for explainability in neural architectures. Additionally, we discuss emerging research in neurosymbolic AI, brain-inspired computing, and ethical considerations in AI decision-making. The paper highlights the transformative potential of AI cognition while addressing its inherent risks and challenges.