3. Outline:
Definition
history
Comparisons between human and
computer intelligence
Branches of A.I
Applications
Outcomes
Advantages & Disadvantages
Future of A.I
Conclusion

4. Definition
• Artificial intelligence (AI) is the intelligence of machines
and the branch of computer science which aims to
create it.
(Wikipedia)
• 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

5. Definition
What is Intelligence ?
 To respond to situations very flexibly.
 To make sense out of ambiguous or contradictory
messages.
 To recognize the 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.

7. History of Artificial Intelligence
 1943 – McCulloh and Pitts, Boolean
circuit model of brain.
 1950 – Turing’
intelligence.
computing
machine
and
 1956 – John McCarthy coined the term "artificial
intelligence" as the topic of the Dartmouth
Conference, the first conference devoted to the
subject

8. History of Artificial Intelligence
 In 1956, computer were solving word problems in
algebra ,proving logical theorems and speaking
English.
 In the early 80`s AI research was received by
commercial success of Expert system .
In the 90`s and Early 21st Century ,,AI achieved its
greatest successes

9. Comparisons between
computer and human
intelligence

10. Comparison
Normal humans have the same intellectual
mechanisms and that differences in intelligence are
related to ``quantitative biochemical and physiological
conditions' , but computer programs have plenty of
speed and memory but their abilities correspond to the
intellectual mechanisms that program designers
understand well enough to put in programs.
Whenever people do better than computers on
some task or computers use a lot of computation to do
as well as people, this demonstrates that the program
designers lack understanding of the intellectual
mechanisms required to do the task efficiently.

11. BRANCHES
•
Logical AI
•
Pattern Recognition
•
Representation
•
Common Sense, Knowledge and Reasoning
•
Planning
•
Epistemology
•
Ontology
•
Heuristics
•
Genetic Engineering

13. APPLICATIONS OF A.I.
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
Phases in Expert 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. APPLICATIONS OF A.I.
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.

15. APPLICATIONS OF A.I.
Natural Language Processing
The goal of NLP is to enable people and computers
to communicate in a natural (humanly) language
rather than in a computer language.
The field of NLP is divided in 2
categories—
 Natural Language understanding.
 Natural Language generation.

16. APPLICATIONS OF A.I.
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 AI helps computer to
understand what they see through
attached cameras.

17. APPLICATIONS OF A.I.
Robotics
A Robot is an electromechanical 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 ‘intelligent’ robot includes
some kind of sensory apparatus that
allows it to respond to change in it’s
environment.

18. OUTCOMES
OF
A.I

19. Advantage

it can help improve our way of life

machines will be able to do jobs that require
detailed instructions
mental alertness and
decision making
capabilities


use robots for heavy
construction, military
benefits, or even for
personal assistance at
private homes

there will be less injuries
and stress to human
beings

20. Advantage
 Many of our health problems now have possible
solutions with the use of Artificial Intelligence in
studies at universities
 scientists have been using AI to test theories
and notions about how our brains work
 AI opens up new and exciting
avenues for entertainment
possibilities.
 AI also makes interactive
electronic games more fun by
making the computer
controlled characters more
realistic and human-like

21. Disadvantage
 Growth of Unemployment rates .
 Enhance laziness in humans.
 Retarding human capabilities.
 Need to restructure the legal system.
 Could be hazardous in Hospitals.

22. FUTURE OF
A.I

23. 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.

24. 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.

25. 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.