McCulloch-Pitts Neuron: Warren McCulloch and Walter Pitts created the first mathematical model of a neural network, demonstrating that simple networks could compute any arithmetic or logical function.

Turing Test: Alan Turing published "Computing Machinery and Intelligence," proposing the famous Turing Test as a criterion for machine intelligence. This paper asked the fundamental question: "Can machines think?"

Dartmouth Conference: John McCarthy, Marvin Minsky, Claude Shannon, and Nathan Rochester organized the Dartmouth Summer Research Project on Artificial Intelligence. This event officially coined the term "Artificial Intelligence" and established AI as an academic discipline.

Perceptron: Frank Rosenblatt invented the Perceptron, the first artificial neural network capable of learning through trial and error. This marked a significant step toward machine learning.

ELIZA: Joseph Weizenbaum created ELIZA, an early natural language processing program that could engage in seemingly intelligent conversation by pattern matching and substitution.

Shakey the Robot: Stanford Research Institute developed Shakey, the first mobile robot capable of reasoning about its actions. It could navigate rooms, turn lights on and off, and move objects.

Expert Systems Boom: AI experienced a renaissance with expert systems like MYCIN (medical diagnosis) and XCON (computer configuration). These systems encoded human expertise in specific domains, proving commercially valuable and attracting renewed investment.

Deep Blue: IBM's Deep Blue defeated world chess champion Garry Kasparov, demonstrating that machines could outperform humans in complex strategic games through brute-force computation and sophisticated evaluation functions.

Statistical Machine Learning: The focus shifted from rule-based systems to statistical approaches. Support Vector Machines, Random Forests, and other algorithms enabled machines to learn patterns from data without explicit programming.

AlexNet: Alex Krizhevsky's deep convolutional neural network won the ImageNet competition by a large margin, sparking the deep learning revolution. This demonstrated that deep neural networks could achieve superhuman performance in image recognition.

AlphaGo: DeepMind's AlphaGo defeated world champion Lee Sedol in Go, a game considered far more complex than chess. This achievement showcased the power of combining deep learning with reinforcement learning.

Transformer Architecture: The introduction of the Transformer architecture revolutionized natural language processing. Models like BERT and GPT demonstrated unprecedented language understanding and generation capabilities.

Large Language Models: GPT-3, GPT-4, and other large language models demonstrated remarkable abilities in text generation, reasoning, and multi-task learning. AI systems began showing emergent capabilities, raising new questions about machine intelligence and consciousness.