Foundations & History
The key historical milestones, paradigm shifts, and inflection points that shaped AI as a field from 1950 to present.
Sub-topics
Alan Turing's 1950 paper 'Computing Machinery and Intelligence' proposed the imitation game as a test for machine intelligence, founding the philosophical basis for AI.
The 1956 Dartmouth workshop coined the term 'Artificial Intelligence' and launched AI as a formal academic discipline. Organized by McCarthy, Minsky, Rochester, and Shannon.
Frank Rosenblatt's 1958 perceptron was the first trainable neural network. Minsky and Papert's 1969 critique of its limitations contributed to the first AI winter.
Triggered by the 1973 Lighthill Report and DARPA funding cuts in 1974. Perceptron limitations and unfulfilled promises led to a collapse of AI research funding.
Revival between the two AI winters. Rule-based expert systems like XCON saved DEC $40M. By 1985, corporations spent over $1B on AI annually.
Collapse of the LISP machine market in 1987 as cheaper workstations emerged. Expert systems proved brittle and expensive to maintain, eroding confidence in AI.
AI shifted from hand-crafted rules to data-driven statistical methods in the 1990s. Machine learning, SVMs, and probabilistic models replaced symbolic approaches.
AlexNet's 2012 ImageNet victory proved deep neural networks could dramatically outperform traditional methods, igniting the modern deep learning era.