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This article traces the evolution of Artificial Intelligence (AI) from its conceptualization to the present-day applications. It begins with the origins of AI, followed by the Dartmouth Conference in 1956, which marked the birth of AI as an interdisciplinary field. Early AI researchers focused on symbolic or rule-based approaches, known as “good old-fashioned AI” (GOFAI). The 1970s and 1980s saw a period known as the “AI winter,” characterized by waning interest and funding due to unmet expectations and overhyped promises. The resurgence of AI in the late 20th century was fueled by advancements in machine learning, which enabled machines to learn from data rather than relying solely on rule-based programming.
