The foundations of AI were laid when Warren McCulloch and Walter Pitts created the first mathematical model of neural networks in 1943. The term "Artificial Intelligence" was coined by John McCarthy at the Dartmouth Conference in 1956, marking the official birth of AI as a field.

This era saw tremendous optimism and breakthroughs. Programs could solve algebra problems, prove theorems, and even speak English. The first AI lab was established at MIT, and funding flourished as researchers believed human-level AI was just around the corner.

Overpromising and underdelivering led to reduced funding and interest. The limitations of early AI became apparent - computers lacked the processing power and data needed to tackle complex problems. This period taught valuable lessons about realistic expectations.

AI experienced a boom with expert systems that could make decisions in specialized domains. Companies invested billions in these knowledge-based systems. The success of systems like XCON showed that AI could deliver real business value.

Geoffrey Hinton's breakthrough in deep learning transformed AI. Neural networks with many layers could learn complex patterns. In 2012, AlexNet won the ImageNet competition, proving that deep learning could outperform traditional computer vision techniques.

AI has become ubiquitous. From AlphaGo defeating world champions to large language models like GPT and Claude demonstrating remarkable capabilities, AI is transforming every industry. The future promises even more revolutionary breakthroughs.