1. ARTIFICIAL INTELLIGENCE

2. What is Artificial
Intelligence?

3. What is AI?
How does
th e h u m a n
b ra in w o rk ?
W h a t is
in te llig e n c e ?
How do we
e m u la te th e
h u m a n b ra in ?
How do we
c re a te
in te llig e n c e ?
W h o c a re s ? L e t’s
do som e cool and
u s e fu l s tu ff!

4. Count…...
 The branch of computer science concerned
with making computers behave like humans
 OR
 The ability of a computer or other machine to
perform those activities that are normally
thought to require intelligence.

5. Count…...
 There are two situation or implementation of
human quality .
 Soft quality
 Physical quality

6. Soft quality
 We can make software for this .

7. Physical quality
 Robotics

8. count…...
 Humanoid robots

9. Researcher
A.I
Strong
A.I.
Weak
A.I.

10. Strong A.I.
 “Strong” AI claims that a digital computer can
in principle be
 programmed to actually be a mind, to be
intelligent, to
 understand, perceive, have beliefs, and
exhibit other
 cognitive states normally ascribed to human
beings.

11. Weak A.I.
 “Weak” AI just claims the digital computer is a
useful tool for
 studying intelligence and developing useful
technology.
 A running AI program is at most a simulation
of a cognitive
 process but is not itself a cognitive process.

12. What is external
input?

13. External Input

14. Branches of A.I
 There are six branches of A.I on which we
focus greatly
1. Natural language processing
2. computer system
3. Learning system
4. Robotics
5. Knowledge Engineering
6. Expert System

15. 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.

16. Computer vision
 The goal of computer vision research is to
give computers this same powerful facility
for understanding their surrounding.

17. Machine learning
 Computer changes how it functions or
reacts to situations based on feedback

18. Robotics
 Mechanical and computer devices that
perform tedious tasks with high precision

19. Knowledge engineering
 KE is an engineering discipline that involves
integrating knowledge into computer
systems in order to solve complex problems
normally requiring a high level of human
expertise

20. Expert System
 An Expert System is a computer program
designed to act as an expert in a particular
domain (area of expertise).

21. Expert
system
Knowledge engineer
Knowledge user

22. NLP
CV
ML
KE
ES
R
60%
software
50%
software
62%
software
59%
software
45%
software
53%
physical

23. Turing Test
 Proposed by Alan Turing(1950), a British
Computer scientist.
 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.

25. Applications of AI
 Military
 “Smart bombs”
 Guided by remote control camera systems
directed to the intended target
 Unmanned drone aircraft
 Missiles fly military missions and launch
weapons from a distance
 Decoding of enemy secret codes
 Rapid translation of foreign language

26. Applications of AI
 Science
 Development of new drugs
 Model clinical studies in animals and humans
 Remote controlled surgical procedures
 Uses robotics and computer-based optical
systems
 Can be performed half-way around the world
 Advanced weather modeling
 Doppler Radar
 Looks at trends and past models to predict
weather patterns

27. Applications of AI
 Industrial
 Machine vision inspection systems
 Cameras and computers are placed on
assembly lines to find defects
 Robotic systems
 Use computer automation and
mechanical equipment
 Take place of humans in manufacturing
of cars

28. Future of AI
 The future is really unknown
 Researchers seem to disagree on a lot of the
same issues
 With the rate at which technology is
improving it is logical to believe AI will
continue to get more and more high degree
complex machine