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The evolution of Artificial Intelligence (AI) has been a captivating journey marked by significant milestones and transformative breakthroughs. Beginning in the mid-20th century with the advent of symbolic AI and early rule-based systems, the field gradually embraced machine learning approaches, symbolized by the development of neural networks and the birth of the subfield of connectionism. The late 20th century witnessed AI's integration into practical applications, such as expert systems and speech recognition. However, a period of limited progress, known as the "AI winter," followed due to unmet expectations. The emergence of powerful computational resources and the adoption of data-driven approaches in the 21st century marked a renaissance in AI, leading to unprecedented achievements in areas like computer vision, natural language processing, and reinforcement learning.
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The evolution of Artificial Intelligence (AI) has been a captivating journey marked by significant milestones and transformative breakthroughs. Beginning in the mid-20th century with the advent of symbolic AI and early rule-based systems, the field gradually embraced machine learning approaches, symbolized by the development of neural networks and the birth of the subfield of connectionism. The late 20th century witnessed AI's integration into practical applications, such as expert systems and speech recognition. However, a period of limited progress, known as the "AI winter," followed due to unmet expectations. The emergence of powerful computational resources and the adoption of data-driven approaches in the 21st century marked a renaissance in AI, leading to unprecedented achievements in areas like computer vision, natural language processing, and reinforcement learning.