The document summarizes the history and development of artificial intelligence from its early beginnings in the 1950s through the present day. It traces influences from various fields like philosophy, mathematics, psychology and economics. Key events and eras discussed include the Dartmouth workshop in 1956, the rise of expert systems in the 1960s-70s, the AI winter of the late 1980s, and the modern focus on data-driven machine learning approaches like deep learning.

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3. CONSUMER
IoT/
MOBILITY
“Software is
eating the world”
“Data is the
new oil”

7. Philosophy Logic, methods of reasoning
Mathematics Algorithms, probability
Psychology Behaviorism, cognitive psychology
Economics Utility/game/decision theory, operations research
Linguistics Grammar, knowledge representation
Control theory Objective functions, feedback loops

8. 1956
Dartmouth
Summer
workshop
1952-1969
Early enthusiasm
Lisp, formal logic vs.
working models
Partially based on Russell & Norvig
1966-1973
Reality sets in
Lack of real world context
Computing power limits
1969-1979
Knowledge-based systems
Expert systems, language
Early-mid 1980s
Becomes an industry
Ambitious goals
Neural nets return
Late 80s
AI winter
Collapse of Lisp machine market
Failures: expert systems, Fifth
Generation project, etc.
1995-
Intelligent agents
Modular approaches
Internet cross-pollination
21st century
Data, data, data
Machine learning
Deep learning

9. Thinking Humanly
Cognitive modeling
Informed by neurophysiology
Thinking Rationally
Logicist tradition
Intelligence based on logical relationships
Acting Humanly
Turing Test
Computer vision, robotics, language, reasoning
Acting Rationally
Rational agent approach
Achieve best or best expected outcome

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19. Backpropagation

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25. Supervised Learning
Reinforcement Learning
(semi-supervised)

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30. http://nautil.us/issue/40/learning/is-artificial-intelligence-permanently-inscrutable

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