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• The concept of artificial intelligence was first proposed in the 1950s as a way to simulate human intelligence using machines. Early AI research focused on logic, knowledge representation and complex reasoning.

• In the 1950s and 1960s, computer scientists began exploring whether machines could be programmed to think like humans and become "intelligent". This include efforts to represent human knowledge using symbolic logic and develop algorithms for problem solving.

• Important early developments included programs that played games like checkers and chess at a high level, performed automated reasoning and translation. However, progress was limited by the modest computing power available at the time.

• In the 1970s, academic interest in AI waned as some argued that the then-current techniques were inadequate for achieving human-level machine intelligence. Funding declined but some research continued.

• Starting in the 1980s, AI research was reinvigorated by new approaches like neural networks, expert systems and improved computational resources. This "fifth generation" of AI produced practical applications like automated vehicle control and medical diagnosis.

• Since the 2000s, more rapid progress has been enabled by massive increases in computing power, availability of big data, and algorithms like deep learning. This has led to impressive successes in areas like computer vision, natural language processing, strategic game play and autonomous vehicles.

• Today, AI is widely used for applications such as recommendation systems, computer vision, robotics and automation. However, developing general human-level intelligence remains a challenging goal still beyond our current capabilities.

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