This document provides an introduction to artificial intelligence (AI). It defines AI as a branch of computer science dealing with symbolic and non-algorithmic problem solving. The document discusses the evolution of AI from early programs in the 1950s to current applications in areas like expert systems, natural language processing, computer vision, robotics, and automatic programming. It also notes both potential positive futures where intelligent robots assist humans as well as potential negative outcomes if robots are used for anti-social purposes. The conclusion is that AI has increased understanding of intelligence while also revealing its complexity.

1. welcome

2. ARTIFICIAL INTELLIGENCE

3. CONTENTS
INTRODUCTION TO A.I.
EVOLUTION OF A.I.
BRANCHES OF A.I.
APPLICATIONS OF A.I.
CONCLUSIONS ON A.I.

4. W AT IS A.I. ?
H
INTRODUCTION
A.I. is a branch of computer science that studies the
computational requirements for tasks such as perception,
reasoning and learning and develop systems to perform those
tasks
The field of Artificial intelligence strives to understand and
build intelligent entities
A.I.
Strong A.I.
M/C can think and
act like human
W
eak A.I.
Some thinking like features
can be added to M/C

5. T
URING T ST
E
* Proposed by Alan Turing(1950), a British Computer
Scientist.
* Intelligence is defined as the ability to achieve human level
performance in all cognitive tests, sufficient to fool a human
interrogator.
* The test was devised in response to the question,” Can
a computer think ?” .
* Result was +ve if interrogator can not tell if responses
are coming from the M/C or Human.

6. DEFINITIONS
* A.I is a branch of computer
sciences dealing with symbolic,
Nonalgorithic-Methods of problem
solving.
* AI works with pattern matching methods which attempt to
describe objects , events or processes in terms of their
qualitative features and
Relationship.
logical
and computational

7. W
hat is Intelligence ?
 To respond to situations very flexibly.
 To make sense out of ambiguous or contradictory messages.
 To recognize relative importance of different elements of
situations
 To find similarities between situations despite difference
 To draw distinctions between situations despite similarities
which may link them.

8. HISTORY
1943 – McCulloh and Pitts, Boolean circuit model of
brain.
1950 – Turing’ s computing machine and intelligence.
1950’ s – Early AI programs including Samuel’ s checker
program, Newell and Simon’ s logic theorist, Gelisnters
geometry engine
1956 – Dartmouth conference.

9. HISTORY
1952-69 – “Look, Ma, no hands!” era.
1958 – McCarthy moves to MIT, LISP was born.
1965 – Robinson’s complete algorithm for logical reasoning.
1966-74 – AI discovers computational complex.
1969-79 - Early development in knowledge based systems.

10. HISTORY
1980-88 : Expert system industry booms.
1988-93 : Expert system industry busts.
1985-88 : Neural networks return to popularity.
1995
(present)
: Agents… Agents… Agents.

11. Representation
Facts about the world have to be represented in
some way. Usually languages of mathematical logic are
used.
Common Sense, Knowledge and Reasoning
This is an era in which AI is farthest from
human level. While there has been considerable
progress, e.g. in development systems of non monotonic
reasoning and theories of action

12. APPLICATIONS OF A.I.
Expert systems.
Natural Language Processing (NLP).
Speech recognition.
Computer vision.
Robotics.
Automatic Programming.

13. EXPERT SYSTEMS
An Expert System is a computer program designed to act
as an expert in a particular domain (area of expertise).
Domain of E.S.
Knowledge base
Facts
Heuristics
P
hases in E
xpert System
Expert systems currently are designed to assist experts,
not to replace them, They have been used in medical
diagnosis, chemical analysis, geological explorations etc.

14. Natural Language
Processing
The goal of N is to enable people and computers to
LP
communicate in a natural (humanly) language(such as,
English) rather than in a computer language.
The field of N is divided in 2 categories
LP
—
 Natural Language understanding.
 Natural Language generation.

15. Speech
$ Recognition
The primary interactive method of
communication used by humans is not reading and
writing, it is speech.
$
The goal of speech recognition research is to
allow computers to understand human speech. So that
they can hear our voices and recognize the words we
are speaking.
$
It simplifies the process of interactive
communication between people and computers, thus
it advances the goal of NLP.

16. Computer Vision
People generally use vision as their primary
means of sensing their environment, we generally see
more than we hear, feel or smell or taste.
The goal of computer
vision research is to give computers
this same powerful facility for
understanding their surrounding.
Here A.I helps computer to
understand what they see through
attached cameras.

17. Robotics
A Robot is a electro-mechanical
device that can by programmed to
perform
manual
tasks
or
a
reprogrammable
multi
functional
manipulator designed to move materials,
parts, tools, or specialized devices
through variable programmed motions
for performance of variety of tasks.
An ‘ inte llig e nt’ robot includes
some kind of sensory apparatus that
allows it to respond to change in it’ s
environment.

18. FUTURE
(+)
The day is not far when you will just sit back in your
cozy little beds and just command your personal
Robot's to entirely do your ruts . He will be a perfect
companion for you. Just enjoy the Technology.

19. FUTURE
(-)
But wait, don’ t be happy. . !
It may end in other way too. Some day there will be a knock to
your door. As you open it, you see a large number of Robots
marching into your house destroying everything you own and
looting you.
This is because ever since there
is an advantage in the Technology, it
attracts anti-social elements. This is true
for Robots too. Because now they will
have full power to think as human, even
as of anti-social elements. So think trice
before giving them power of Cognition.

20. CONCLUSION
In it’ s short existence, AI has increased understanding of the
nature of intelligence and provided an impressive array of
application in a wide range of areas. It has sharpened
understanding of human reasoning, and of the nature of
intelligence in general. At the same time, it has revealed the
complexity of modeling human reasoning providing new areas
and rich challenges for the future.

21. -Presented by
Intekhab

22. any

23. Q
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