1.1
Origin & Definition of AI
Artificial intelligence (AI) is not new. The term was coined
in 1956 by John McCarthy, a Stanford computer science
professor who organized an academic conference on the
topic at Dartmouth College in the summer of that year.
The field of AI has gone through a series of boom-bust
cycles since then, characterized by technological break-
throughs that stirred activity and excitement about the
topic, followed by subsequent periods of disillusionment
and disinterest known as 'AI Winters' as technical limita-
tions were discovered. As you can see in figure 1, today
we are once again in an 'AI Spring'.
Artificial intelligence can be defined as human intelligence
exhibited by machines; systems that approximate, mimic,
replicate, automate, and eventually improve on human
thinking. Throughout the past half-century a few key com-
ponents of AI were established as essential: the ability to
perceive, understand, learn, problem solve, and reason.
Countless working definitions of AI have been proposed
over the years but the unifying thread in all of them is
1 UNDERSTANDING ARTIFICIAL INTELLIGENCE
Understanding Articial Intelligence 3
that computers with the right software can be used to
solve the kind of problems that humans solve, interact
with humans and the world as humans do, and create
ideas like humans. In other words, while the mechanisms
that give rise to AI are ‘artificial’, the intelligence to which
AI is intended to approximate is indistinguishable from
human intelligence. In the early days of the science, pro-
cessing inputs from the outside world required extensive
programming, which limited early AI systems to a very
narrow set of inputs and conditions. However since then,
computer
science has worked to advance the capability of
AI-enabled
computing systems.
Board games have long been a proving ground for AI
research, as they typically involve a finite number of
players, rules, objectives, and possible moves. This essen-
tially means that games – one by one, including checkers,
backgammon, and even Jeopardy! to name a few – have
been taken over by AI. Most famously, in 1997 IBM’s Deep
Blue defeated Garry Kasparov, the then reigning world
champion of chess. This trajectory persists with the ancient
Chinese game of Go, and the defeat of reigning world
champion Lee Sedol by DeepMind’s AlphaGo in March 2016.
Figure 1: An AI timeline; Source: Lavenda, D. / Marsden, P.
AI is born
Focus on specic intelligence
Focus on specic problems
The Turing Test
Dartmouth College conference
Information theory-digital signals
Symbolic reasoning
Expert systems & knowledge
Neural networks conceptualized
Optical character recognition
Speech recognition
Machine learning
Deep learning: pattern analysis & classification
Big data: large databases
Fast processors to crunch data
High-speed networks and connectivity
AI Winter I AI Winter II
1964
Eliza, the first chatbot
is developed by Joseph
Weizenbaum at MIT
1997
IBM's Deep Blue defeats
Garry Kasparov, the world's
reigning chess champion
Edward Feigenbaum
develops the first
Expert System,
giving rebirth to AI
1975 – 1982
IBM's Watson Q&A machine wins Jeopardy!
Apple integrates Siri, a personal voice
assistant into the iPhone
2011
2016
AlphaGo
defeats Lee Sedol
1950 1960 1990 2010 2020
2000
19801970
2014
YouTube recognizes
cats from videos
Dartmouth conference
led by John McCarthy
coins the term
"artificial intelligence"
1956
Real-world problems are complicated
Facial recognition, translation
Combinatorial explosion
Limited computer processing power
Limited database storage capacity
Limited network ability
Disappointing results: failure to achieve scale
Collapse of dedicated hardware vendors
THE RISE OF AI
