Abstract
Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies reshaping industries and society. This paper explores the foundational concepts of AI and ML, emphasizing their definitions, methodologies, and applications. AI encompasses a broad spectrum of techniques aimed at mimicking human intelligence, while ML, a subset of AI, focuses on the development of algorithms that enable machines to learn from data. We examine the historical evolution of these fields, the current state of research, and key technologies such as neural networks, natural language processing, and computer vision. The implications of AI and ML are vast, impacting sectors including healthcare, finance, and transportation, and raising ethical considerations regarding privacy, bias, and employment. By analyzing case studies and recent advancements, this paper aims to highlight the potential and challenges of integrating AI and ML into everyday life, paving the way for future research and development in this dynamic domain
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