Information about Artificial Intelligence.

1. Artificial Intelligence
Presented by:- Rohan Vadsola

2. Content:-
•Introduction
•History
•Branches of AI
•Planning
•Understanding
•Natural language Processing
•Knowledge Representation
•Neural Networks
•Common Sense
•Applications
•Conclusion

3. Introduction:-
 It is the science and engineering of making
intelligent machines, especially intelligent
computer programs.
 Its task is using computers to understand human
intelligence.
 Ability to achieve goals in the world.
 AI is the study of how to make computers do
things which, at the moment, people do better.

4. History:-
 English mathematician Alan Turing was the first who
gave lecture on it in 1947.
 By the late 1950s, there were many researches on AI, on
programming computer.
 The branch of computer science concerned with
making computers behave like humans.
 The term was coined in 1956 by John McCarthy at the
Massachusetts Institute of Technology.
 In 1974 Paul John Werbos describe algorithm for AI
programming.

5. Branches of AI:-
 Perceptive system:- A system that approximates the
way a human sees, hears, and feels objects.
 Vision system:-Captures, store and manipulate visual
images and pictures.
 Robotics:-Mechanical and computer devices that
perform tedious tasks with high precision
 Expert system:- Stores knowledge and makes
inferences.
 Learning system:-Computer changes how it functions
or reacts to situations based on feedback

6. Cont….
 Natural language processing:-Computers understand
and react to statements and commands made in a
“natural” language such as English.
 Neural network:-Computer system that can act like or
simulate the functioning of the human brain.

7. Planning:-
 The word planning refers to the process of computing
several steps of a problem solving procedure before
executing any of them.
 Planning of a problem is done in a hierarchical
manner.
 A hierarchical control system is a form of control
system in which a set of devices and governing
software is arranged in a hierarchy.

10. Components of a planning system:-
 Choose the best rule to apply next based on the best
available information
 Apply the chosen rule to compute the new problem
state that arises from its application
 Detect when a solution has been found
 Detect dead ends so that they can be abandoned and
the system’s effort directed in more fruitful directions
 Detect when an almost correct solution has been
found and employ special technique to make it totally
correct.

11. Understanding:-
 To understanding something is to transform it from
one representation into another
 Understanding is defined as the process of mapping
into appropriate actions
 Computer understanding has so far been applied
primarily to images, speech, and typed language.

12. What makes understanding hard:-
 There are four major factors that contribute to the
difficulty of an understanding problem:-
1. The complexity of the target representation into which
the matching is being done
2. The type of the mapping : one-one, many-one, or
many-many
3. The level of interaction of the components of the
source representation
4. The presence of noise in the input to the understander

13. Natural language processing:-
 Language is meant for communicating about the world.
 Natural language processing gives machines the ability to
read and understand the languages that humans speak.
 A sufficiently powerful natural language processing system
would enable natural language user interfaces and the
acquisition of knowledge directly from human written
sources, such as internet texts.
 Some straightforward applications of natural language
processing include information retrieval and machine
translation.

14. Example:-
 The problem: The same expression means different
contexts:
1.where’s the water?(in a chemistry lab, it must be pure)
2.where’s the water?(when you are thirsty, it must be potable)
3. where’s the water?(dealing with a leaky roof, it can be
filthy)
 The good side: Language lets us communicate about an
infinite world using a finite number of symbols.

15. Knowledge Representation:-
 An ontology represents knowledge as a set of concepts
within a domain and the relationships between those
concepts.
 A representation of "what exists” is an ontology.
 Knowledge Representation and knowledge
engineering are central to AI research.
 Among the things that AI needs to represent are:
objects, properties, categories, and relations between
objects, situations, events, states and time, causes and
effects.

17. Neural Networks:-
 A neural network is an interconnected group of nodes,
akin to the vast network of neurons in the human
brain.
 The study of artificial neural network began in the
decade before the field AI research was founded.
 The main categories of network are acyclic or feed
forward neural networks(Where the signal passes in
only one direction) and recurrent neural
networks(which allow feedback).

18. Interconnected nodes of neural
networks:-

19. Commonsense:-
 Commonsense is the basic ability to perceive,
understand and judge things which is shared by nearly
all people and reasonably expected.
 Today all smartly running machines run on the power
of commonsense.
 A computer that interacts with the real world must be
able to reason about things like time, space, and
materials.

20. Cont……
 Commonsense helps a machine to solve a problem on
its own by fitting such circuits into a machine.

21. Applications:-
 Artificial intelligence has been used in a wide range of
fields including medical diagnosis, stock trading,
robot control, law , remote sensing, scientific discovery
and toys.
 Some applications are as follows:-
1. Finance
2. Hospitals and medicines
3. Heavy industry
4. Online and telephone customer service
5. Toys and games

22.  Finance:-
a. Banks use AI systems to organize operations , invest in
stocks, and manage properties.
 Hospitals and medicines:-
a. A medical clinic can use AI systems to organize bed
schedules, make a staff rotation, and provide medical
information.
b. Artificial neural networks are used as clinical decisions
support systems for medical diagnosis, such as in
concept processing technology in EMR software.

23. Cont…..
 Heavy industry:-
a. Robots have become common in many industries.
b. They are often given jobs that are considered
dangerous to humans.
c. Robots have proven effective in jobs that are very
repetitive which may lead to mistakes or accidents due
to a lapse in concentration and other jobs which
humans may find degrading.

24. Cont.….
 Online and telephone customer service:-
a. AI techniques is used in answering machines of call
centre, such as speech recognition software to allow
computers to handle first level of customer support,
text mining and natural language processing to allow
better customer handling.
Example of online gift shop

25. Cont….
 Toys and games:-
a. AI is also used in field to entertainment for children.
b. Many domestic robots and a large variety of game are
developed.
c. For example, a robotic dog ,cat and fish with
intelligent features.

26. Conclusion:-
 Artificial intelligence and technology are one side of
the life that always interest and surprise us with the
new ideas , topics , innovations, products..etc.
 AI is still not completely implemented , however there
are many important tries to reach the level and to
compete in market , like sometimes the robots that are
shown in TV .