The document presents an overview of artificial intelligence (AI), covering its definition, history, key contributors, and various applications across fields such as robotics, medicine, and natural language processing. It discusses challenges in AI, including specific problems researchers aim to solve, and compares AI with human intelligence. The conclusion emphasizes both the potential and limitations of AI, suggesting a bright future despite current challenges.

1. Presented by
Prince kumar kushwaha
0902EC101053
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2. 1 What Is Artificial Intelligence
2 History
3 Scientist In Creation Of AI
4 Problems Of AI
5 The Turing’s Test, Picture Arrangement Test
6 Artificial Intelligence Vs Human Intelligence
7 Artificial Intelligence Applications
8 Future Of AI
9 Advantages And Disadvantages Of AI
10 Conclusion
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3. Artificial intelligence (AI) is the
intelligence exhibited by machines or
software, and the branch of computer
science that develops machines and
software with human-like
intelligence.
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4. HISTORY
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5. SCIENTIST IN CREATION OF AI
In 1956 John McCarthy regarded as
the father of AI, organized a
conference to draw the talent and
expertise of others interested in
machine intelligence.
John McCarthy, who defines the term
as "the science and engineering of
making intelligent machines".
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6. Problems of AI
The general problem of simulating intelligence has been
broken down into a number of specific sub-problems. These
consist of particular traits or capabilities that researchers
would like an intelligent system to display.
Deduction, reasoning, problem solving
Knowledge Representation
Planning
Learning
Natural language processing
Motion and manipulation4/19/2014 6

7. 1 Deduction, reasoning, problem solving
Early AI researchers developed Algorithms
that imitated the step-by-step reasoning that
human beings use when they solve puzzles,
play board games or make logical
deductions.
2 Knowledge Representation
Many of the problems machines are
expected to solve will require4/19/2014 7

8. 3 Planning
Intelligent agents must be able to set goals
and achieve them. They need a way to visualize
the future and be able to make choices that
maximize the utility (or "value") of the available
choices.
Types of planning
1 Classical planning 2
Multi agent planning
4 Learning
Machine learning is the study of computer
algorithms that improve automatically through
experience and has been central to AI research
since the field's inception.
Types of learning
1 Unsupervised learning4/19/2014 8

9. 5 Natural language processing
Natural language processing gives machines
the ability to read and understand the
languages that the human beings speak.
6 Motion and manipulation
The field of robotics is closely related to AI.
Intelligence is required for robots to be able to
handle such tasks as object manipulation and
navigation, with sub-problems of localization
(knowing where you are), mapping (learning
what is around you) , motion planning (figuring
out how to get there) and path planning (going
from one point in space to another point).4/19/2014 9

10. The Turing’s Test
 Alan Turing (1912 - 1954)
 Proposed a test - Turing’s
Imitation Game
 Tests the intelligence of
the computer.
 Phase 1:
 Man and woman
separated from an
interrogator.
 The interrogator types in
a question to either
party.
 By observing responses,
the interrogator’s goal
was to identify which
was the man and which
was the woman.
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11.  Phase 2 of the Turing’s test:
 The man was replaced by
the computer.
 If the computer could fool the
interrogator as often as the
person did, it could be said
that the computer had
displayed intelligence.
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12. Picture Arrangement
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13. Picture Arrangement
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14. Artificial Intelligence Vs
Human Intelligence
AI
 Exact information .
 Byte-addressable memory.
 hardware/software used.
 Not forget and lose information.
HI
 Not exact information.
 Content-addressable memory.
 No hardware/software used.
 Can forget and lose information
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15. Approaches to AI
Methods and ways used to solve AI problems
• cybernetics
• cognitive simulation
• logic based
• knowledge based
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16. Cybernetics
It is the study of control and communication in the animal
and machine.
Cognitive simulation
Psychology was the base of this approach to AI.
Human psychology was simulated.
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17. Logic based
This approach uses formal logic to solve a wide variety
of problems, Including knowledge representation, planning
and learning. programming language used is PROLOG
Knowledge based
Expert systems were developed keeping knowledge as the base,
these systems could behave like an human expert and
answer or provide solutions to any questions related to that field
to which it is intended.
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18. 1 ROBOTICS
2 MILITARY
3 MEDICINE
4 NATURAL LANGUAGE PROCESSING
5 PATTERN RECOGNITION
6 TELEPHONE TRANSLATORS
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19. Advantages
Don’t need sleep
Easier copying
Save the time
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20. Disadvantages
It will take long time to build
Small amount of information
Can’t provide a human feel
No emotional understanding
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21. AI is like a two edged sword, at one end they can
solve problems "intelligently" at another end they
pose a problem themselves.
A.I. is something that has been achieved only
to a very limited degree and it remain a very
difficult problem and a long term goal of
computer science.
Since we are having some limitation or
disadvantages of A.I. but still there is a
bright future of Artificial Intelligence.
CONCLUSION
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22. Just You Wait...
or 20...
or 30...
or 50...
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23. 4/19/2014 23

24. ANY QUERY …
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