History of AI

Detailed chronological timeline of AI history as discussed in Peter Norvig and Stuart Russell's
book, "Artificial Intelligence: A Modern Approach," including key theories, systems, and
developments:

1940s: The Dawn of AI

• Year: 1943
o Researcher: Warren McCulloch and Walter Pitts
o System/Theory Proposed: McCulloch-Pitts Neuron [link]
o Remarks: Proposed the first mathematical model of a neuron, laying the
foundation for neural networks.
• Year: 1949
o Researcher: Donald Hebb
o System/Theory Proposed: Hebbian Learning [link]
o Remarks: Introduced the idea that neural pathways strengthen as they are
used more frequently, a principle that became fundamental in learning
algorithms.

1950s: The Birth of AI

• Year: 1950
 o Researcher: Alan Turing
o System/Theory Proposed: Turing Test [link]
o Remarks: Proposed a test to determine a machine's ability to exhibit intelligent
behavior indistinguishable from that of a human.
• Year: 1956
o Researcher: John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude
Shannon
o System/Theory Proposed: Dartmouth Conference [link]
o Remarks: This conference is considered the birth of AI as a field, where the term
"Artificial Intelligence" was coined.
• Year: 1957
o Researcher: Frank Rosenblatt
o System/Theory Proposed: Perceptron [link]
o Remarks: Developed the Perceptron, an early neural network model capable of
learning binary classifications. It was an essential step in the evolution of
machine learning.

1960s: The Golden Age of AI

• Year: 1961
o Researcher: James Slagle
o System/Theory Proposed: SAINT (Symbolic Automatic Integrator) [link]
o Remarks: An early AI program designed to perform symbolic integration in
calculus.
• Year: 1965
o Researcher: Joseph Weizenbaum
o System/Theory Proposed: ELIZA [link] [demo]
o Remarks: Developed ELIZA, one of the first chatbots, which simulated
conversation by matching user input to pre-written scripts.
• Year: 1966
o Researcher: Ross Quillian
o System/Theory Proposed: Semantic Memory [link1] [link2] [link3]
o Remarks: Proposed the concept of semantic memory, a model for representing
knowledge as a network of nodes and links.
• Year: 1968
o Researcher: Marvin Minsky and Seymour Papert
o System/Theory Proposed: Perceptrons (Book) [link]
o Remarks: Published a critical analysis of the limitations of perceptrons,
particularly in handling non-linear separability, which led to a temporary decline
in neural network research.

1970s: The First AI Winter

• Year: 1972
o Researcher: Alain Colmerauer and Philippe Roussel
o System/Theory Proposed: Prolog
 o Remarks: Developed Prolog, a logic programming language that became
influential in AI research, particularly in natural language processing.
• Year: 1973
o Researcher: Sir James Lighthill
o System/Theory Proposed: Lighthill Report
o Remarks: A report commissioned by the British government criticized the
progress and promises of AI, leading to a reduction in funding and the first AI
winter—a period of reduced interest and investment in AI research.
• Year: 1979
o Researcher: Hans Moravec
o System/Theory Proposed: Stanford Cart
o Remarks: Developed the Stanford Cart, an early autonomous vehicle capable of
navigating simple obstacles, a precursor to modern robotics.

1980s: The Expert Systems Era

• Year: 1980
o Researcher: Edward Feigenbaum and Bruce Buchanan
o System/Theory Proposed: Expert Systems (DENDRAL, MYCIN)
o Remarks: Pioneered expert systems like DENDRAL for chemical analysis and
MYCIN for medical diagnosis, marking a shift toward applied AI.
• Year: 1982
o Researcher: John Hopfield
o System/Theory Proposed: Hopfield Network
o Remarks: Introduced a form of recurrent neural network, useful in associative
memory and optimization problems.
• Year: 1986
o Researcher: David Rumelhart, Geoffrey Hinton, and Ronald Williams
o System/Theory Proposed: Backpropagation Algorithm
o Remarks: Published a landmark paper on the backpropagation algorithm,
allowing for the training of multi-layer neural networks, sparking renewed
interest in neural networks.

Late 1980s to Early 1990s: The Second AI Winter

• Year: Late 1980s - Early 1990s
o Event: Second AI Winter
o Remarks: The limitations of expert systems, combined with economic factors,
led to a second AI winter. Funding and interest in AI research dwindled during
this period as the promises of AI seemed unfulfilled.

1990s: The Rebirth of AI

• Year: 1993
o Researcher: Rodney Brooks
o System/Theory Proposed: Behavior-Based Robotics
 o Remarks: Proposed a new approach to robotics emphasizing simple, reactive
behaviors rather than complex planning, influencing modern autonomous
systems.
• Year: 1995
o Researcher: Richard Sutton and Andrew Barto
o System/Theory Proposed: Reinforcement Learning (TD-Gammon)
o Remarks: Developed Temporal Difference Learning, a key component of
reinforcement learning, exemplified in TD-Gammon, a backgammon-playing AI.
• Year: 1997
o Researcher: IBM (Deep Blue team)
o System/Theory Proposed: Deep Blue
o Remarks: Defeated Garry Kasparov in a chess match, showcasing AI’s capability
in strategic decision-making. This victory marked the beginning of broader
public recognition of AI's potential.

2000s: The Rise of Machine Learning

• Year: 2001
o Researcher: Cynthia Breazeal
o System/Theory Proposed: Kismet
o Remarks: Developed Kismet, a robot designed to interact socially with humans,
exploring the field of social robotics.
• Year: 2006
o Researcher: Geoffrey Hinton, Yoshua Bengio, Yann LeCun
o System/Theory Proposed: Deep Learning Revival
o Remarks: Sparked renewed interest in deep learning, particularly with
advances in training deep neural networks using GPUs. This period marks the
beginning of the modern era of AI.

2010s: The Deep Learning Era

• Year: 2011
o Researcher: IBM Watson Team
o System/Theory Proposed: Watson
o Remarks: Watson defeated human champions in Jeopardy!, demonstrating AI's
capability in natural language understanding and retrieval -based question
answering.
• Year: 2012
o Researcher: Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton
o System/Theory Proposed: AlexNet
o Remarks: Developed AlexNet, a deep convolutional neural network that won
the ImageNet competition, marking a breakthrough in computer vision.
• Year: 2014
o Researcher: Ian Goodfellow et al.
o System/Theory Proposed: Generative Adversarial Networks (GANs)
 o Remarks: Introduced GANs, a framework where two neural networks contest
with each other, leading to significant advancements in generative modeling.
• Year: 2016
o Researcher: AlphaGo team (DeepMind)
o System/Theory Proposed: AlphaGo
o Remarks: Defeated world champion Lee Sedol in the game of Go,
demonstrating AI's ability to master complex games with deep learning and
reinforcement learning.
• Year: 2018
o Researcher: OpenAI
o System/Theory Proposed: GPT (Generative Pre-trained Transformer)
o Remarks: Released GPT, a large language model that set new benchmarks in
natural language processing.