Abstract

Artificial Intelligence (AI) has evolved from symbolic reasoning systems to advanced generative models and autonomous agents. This paper reviews the historical development of AI, including foundational contributions in machine intelligence, machine learning, deep learning, transformer architectures, and large language models. The study examines major AI paradigms, highlights key application areas, and discusses emerging technologies such as multimodal AI and autonomous agents. Furthermore, the paper analyzes challenges including explainability, bias, privacy, hallucinations, and computational requirements. Finally, the review identifies the future research directions focused on trustworthy, responsible, and human-centered AI systems.

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