Abstract: From early rule-based systems to sophisticated deep learning architectures supporting today's most advanced applications, artificial intelligence (AI) has fast progressed. This work offers a thorough investigation of the several forms of artificial intelligence depending on their functionality and cognitive capacity. From reactive machines and restricted memory systems to theoretical concepts including artificial general intelligence (AGI) and artificial superintelligence (ASI), we explore the historical development of artificial intelligence. After a synthesis of the most important results, the research approach consists in a thorough evaluation of foundational papers and the most recent investigations. Results show that even if restricted artificial intelligence rules contemporary applications (e.g., natural language processing, computer vision, and autonomous systems), major obstacles still exist for the evolution of AGI and self-aware systems. Furthermore, influencing the upcoming generation of intelligent systems are developing themes include neuro symbolic integration, edge artificial intelligence (XAI) and explainable artificial intelligence (XAI). As artificial intelligence develops, the conversation emphasizes ethical, transparent, and biassed problems that have to be resolved. At last, we suggest future directions of research to close present gaps and guarantee that artificial intelligence develops in a way that is both technically strong and morally sound.
Keywords: Artificial Intelligence, Narrow AI, Artificial General Intelligence, Superintelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Neuro symbolic AI, Edge AI, Explainable AI
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DOI:
10.17148/IJARCCE.2025.14221
