Lecture 1 Introduction to AI very basics.ppt

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1. Artificial Intelligence
(AI)
Lecture No. 1

2. Agenda
Intelligence
Intelligence of computer
Artificial intelligence
Intelligent computing Vs Conventional computing
Contribution of other fields to AI
+History of AI
+Applications of AI
References
End
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3. Intelligence?
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4. Can Intelligence be defined?
Intelligence can not be defined abstractly/ precisely.
There are probably as many definitions of intelligence as there
are experts of this field.
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5. Intelligence (definition)
from "Mainstream Science on Intelligence"
(1994), an editorial statement by fifty-two
researchers:
A very general mental capability that, among other
things, involves the ability to reason, plan, solve
problems, think abstractly (conceptually),
comprehend complex ideas, learn quickly and learn
from experience.
(Gottfredson, L.S., 1997).
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6. 6March 6, 2025

7. Intelligence
from "Intelligence: Knowns and Unknowns"
(1995), a report published by the Board of
Scientific Affairs of the
American Psychological Association:
Individuals differ from one another in their ability
to understand complex ideas, to adapt effectively
to the environment, to learn from experience, to
engage in various forms of reasoning, to overcome
obstacles by taking thought.
(Neisser, 1997) and (Perloff, 1996)
7March 6, 2025

8. Other definitions of intelligence
capacity for learning, reasoning, understanding, and
similar forms of mental activity; aptitude (ability) in
grasping truths, relationships, facts, meanings, etc.
the faculty of understanding.
knowledge of an event, circumstance, etc., received
or imparted; news; information.
the gathering or distribution of information,
especially secret information

www. dictionary.com
8March 6, 2025

9. Intelligence (summary)
Intelligence is the ability of:
abstract thought
understanding
communication
reasoning
learning
planning
problem solving
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10. Intelligence of computer
According to the British computer scientist
Alan Turing's test in (1950):
“a computer would deserves to be called
intelligent if it could deceive a human into
believing that it was human.”
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11. Artificial Intelligence?
???
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12. Artificial Intelligence
“A branch of a computer science which studies
the development of software and hardware
which simulates human intelligence”
(Dr. Ghassan Issa)
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13. Artificial Intelligence
AI is the part of computer science concerned with
designing intelligent computer systems, that is,
computer systems that exhibit the characteristics we
associate with intelligence in human behavior-
Understanding languages,
learning,
reasoning,
solving problems, and so on.
(Barr and Feigenbaum, 1981)
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14. 14March 6, 2025
Other Definitions of AI ….
“AI is the study of how to make computer do
things at which, at the moment, people are
better”
(Rich and Knight, 1991)
“AI is study of idea that enable computers to
be intelligent”
(Patrick H. Winston)

15. Intelligent computing Vs Conventional
computing
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  Intelligent
Computing
  Conventional
Computing
1Does
not always guarantee
a
solution to a given
problem.
1Always
guarantees a
solution
to a given
problem.
2Results
may not be reliable
and
consistent
2Results
are consistent and
reliable.
3Programmer
does not tell
the
system how to solve the
given
problem.
3Programmer
tells the
system
exactly how to solve
the
problem
4Can
solve a range of
problems
in a given
domain.
4Can
solve only one
problem
at a time in a
given
domain

16. Intelligent computing Vs Conventional
computing …
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Conventional:
Based on algorithms whose instructions are stored
in memory and executed in sequential way.
AI Computing:
Not based on algorithms but based on:
Knowledge base (symbolic representation)
Uses reasoning and inferencing over the knowledge
base to search and perform pattern matching.

17. Intelligent computing Vs Conventional
computing …
17March 6, 2025

18. Types of AI
All artificial intelligence systems - real and
hypothetical - fall into one of three types:
Artificial
narrow intelligence
 
(ANI), which
has a narrow range of abilities;
Artificial
general intelligence
 
(AGI), which is
on par with human capabilities; or
Artificial
superintelligence
 
(ASI), which is
more capable than a human.
18March 6, 2025 What are the 3 types of AI? A guide to narrow, general, and super artificial intelligence | Codebots

19. 1. Artificial Narrow Intelligence
Artificial narrow intelligence (ANI), also referred to
as weak AI or narrow AI.
The only type of artificial intelligence we have
successfully realized to date.
Narrow AI is goal-oriented, designed to perform
singular tasks - i.e. facial recognition, speech
recognition/voice assistants, driving a car, or
searching the internet - and is very intelligent at
completing the specific task it is programmed to do.
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20. 2. Artificial General Intelligence
Artificial general intelligence (AGI), also referred to
as strong AI or deep AI.
It is the concept of a machine with general
intelligence that mimics human intelligence and/or
behaviours, with the ability to learn and apply its
intelligence to solve any problem.
AGI can think, understand, and act in a way that is
indistinguishable from that of a human in any given
situation.
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21. 2. Artificial General Intelligence
Fujitsu-built K, one of the fastest supercomputers, is one of the
most notable attempts at achieving strong AI, but considering
 
it took 40 minutes to simulate a single second of neural activity
, it is difficult to determine whether or not strong AI will be
achieved in our foreseeable future.
K is upgraded now to Fugaku
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22. 3. Artificial Superintelligence
 
Artificial super intelligence (ASI), is the
hypothetical AI that doesn’t just mimic or
understand human intelligence and behaviour; ASI
is where machines become self-aware and surpass
the capacity of human intelligence and ability.
Superintelligence has long been a fiction in which
robots overrun, overthrow, and/or enslave humanity.
The concept of artificial superintelligence sees AI
will evolve to human emotions and experiences, that
it doesn’t just understand them, it evokes emotions,
needs, beliefs and desires of its own.
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23. Gary Kasparov, world chess champion
in Munich, Germany(2020)
 we have more to win than lose when it comes to AI,
and that rather than becoming obsolete, humans are
going to be promoted.
“Jobs don’t disappear, they evolve. Deleting people
from repetitive jobs frees them up to be more
creative. The future of the human race is there in
creativity.
“The future is about humans and machines working
together. AI will bring you what you want the
most…time.” 23March 6, 2025

24. Applications of AI
Game
playing
General
problem solving
Expert
system
Natural
language Processing
Computer
vision
Robotics
Education
Others
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25. Game Playing
Game
Playing
 
is an important domain
of
 
artificial
intelligence
.
Games don't require much knowledge; the
only knowledge we need to provide is the
rules, legal moves and the conditions of
winning or losing the
 
game.
Generate procedure so that only good moves
are generated
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26. General problem solving
In computer science,
 
problem-solving 
refers
to
 
artificial
intelligence
 
techniques, including
various techniques such as forming efficient
algorithms, heuristics, and performing root cause
analysis to find desirable solutions
A
 
problem 
consists of 
five 
parts: The state space, an
initial situation, actions, a goal test, and path costs.
Chess, Tower of Hanoi Problem, Travelling
Salesman Problem, Water-Jug Problem etc.
26March 6, 2025 Problem Solving Techniques in Artificial Intelligence (AI) | PDF.co

27. Expert Systems
In artificial intelligence, an expert system is a
computer system emulating the decision-making
ability of a human expert.
Expert systems are designed to solve complex
problems by reasoning through bodies of
knowledge, represented mainly as if–then rules
rather than through conventional procedural
code.
 
Wikipedia
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28. Natural language processing 
(
NLP)
Natural
language processing
 
(
NLP) is a
subfield of linguistics, computer science,
and
 
artificial
intelligence
 
concerned with the
interactions between computers and
human
 
language, in particular how to program
computers to process and analyze large
amounts of
 
natural
language
 
data.
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29. Computer Vision
Computer
vision
 
is defined as “a subset of
mainstream
 
artificial
intelligence
 
that deals
with the science of making
 
computers 
or
machines visually enabled, i.e., they can
analyze and understand an image.
Computer vision is an interdisciplinary
scientific field that deals with how computers
can gain high-level understanding from digital
images or videos.
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30. Robotics
Robotics 
is a domain in 
artificial
intelligence
 
that deals
with the study of creating
 
intelligent 
and efficient 
robots.
 Robotics 
and 
artificial
intelligence
 
are really two separate
things.
 
Robotics 
involves building 
robots 
physical
whereas
 
AI 
involves programming 
intelligence.
Artificial
Intelligence
 
or 
AI 
gives 
robots 
a computer
vision to navigate, sense and calculate their reaction
accordingly.
 
Robots 
learn to perform their tasks from humans through
machine learning which again is a part of computer
programming and
 
AI.
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31. Education
Artificial
intelligence can automate basic activities in
education,
like grading.
Educational
software can be adapted to student needs.
It
can point out places where courses need to improve
Students
could get additional support from AI tutors.
AI-driven
programs can give students and educators
helpful
feedback.
AI
may change where students learn, who teaches them,
and
how they acquire basic skills.
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32. Contributions of other disciplines to AI
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Philosophy Logic, methods of reasoning, mind as physical
system, foundations of learning, language,
rationality (wisdom)
Mathematics Formal representation and proof of algorithms,
computation, (un)decidability, (in)tractability,
probability
Economics utility, decision theory
Neuroscience how do brain process information (neuron operation)
Psychology 1- How do humans and animals think and act
2- phenomena of perception and motor control,
experimental techniques
Computer
engineering
building fast computers
Control
theory
1- How can artifacts (objects) operate under their own
control?
2- design systems that maximize an objective
function over time.
Linguistics knowledge representation, grammar

33. Abridged history of artificial intelligence
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1941first electric computer was developed
1943 McCulloch & Pitts:
Boolean circuit model of brain
1949first “stored program” computer was introduced
1950 Turing proposed his “Turing Test” for
intelligence.
1955early chess playing programs demonstrated
1956in Dartmouth conference birth was given to:
"Artificial Intelligence"
1957LISP language by John McCarthy at MIT

34. Abridged history of artificial intelligence
1965expert system DENDRAL started at Stanford
1965Robinson's complete algorithm for logical
reasoning
1966expert system MACSYMA started at MIT
1969—79 Early development of knowledge-based
systems
1970implementation of the Prolog language
1972expert system MYCIN developed at Stanford
1972SHRDLU natural language robot demonstrated at
MIT
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35. Abridged history of artificial intelligence
1980-- AI becomes an industry
1981--Commercial NLP system “Intellect” available
from NLP group
1986-- Neural networks return to popularity
1987--AI becomes a science
1995--The emergence of intelligent agents
1995-2007HLAI (Human Level AI):
AI should return to its roots of striving "machines that
think, that learn”
 Hays and Efros (2007)
 discuss the problem of filling in holes in a photograph
35March 6, 2025

36. Abridged history of artificial intelligence
2008--Artificial General
Intelligence or AGI
AGI looks for a universal algorithm for learning and acting in
any environment
2009 :Google builds self driving car
2011–2014 : Apple's Siri (2011), Google's Google Now (2012)
and Microsoft's Cortana (2014) are smartphone apps that use
natural language to answer questions, make recommendations
and perform actions.
2018: Alibaba language processing AI outscores top humans at a
Stanford University reading and comprehension test, scoring
82.44 against 82.304 on a set of 100,000 questions.
2020: Extensive use of AI in industry and businesses like JD,
Alibaba, Amazon, Daraz etc
36March 6, 2025

37. References
Gottfredson, L.S. (1997). "Foreword to "intelligence and social policy"" Intelligence 24 (1):
1–12. doi:10.1016/S0160-2896(97)90010-6.
http://www.udel.edu/educ/gottfredson/reprints/1997specialissue.pdf.
Neisser, U.; Boodoo, G.; Bouchard Jr, T.J.; Boykin, A.W.; Brody, N.; Ceci, S.J.; Halpern,
D.F.; Loehlin, J.C.; Perloff, R.; Sternberg, R.J.; Others, (1998). "Intelligence: Knowns and
Unknowns". Annual Progress in Child Psychiatry and Child Development 1997.
ISBN
 9780876308707. http://books.google.com/?
id=gLWnmVbKdLwC&pg=PA95&dq=Intelligence:+Knowns+and+unknowns.
Perloff, R.; Sternberg, R.J.; Urbina, S. (1996). "Intelligence: knowns and unknowns".
American Psychologist 51.
Dr. Ghassan Issa, Artificial intelligence, retrieved from: http://www.uop.edu.jo/issa/ai/ai-
part1.htm, retrieved date: 04 Oct, 2011.
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38. References
Crash Course in Artificial Intelligence and Expert systems by Louise E.
Frenzel.
Chapter No.1
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39. 39March 6, 2025
Question????

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The end