1 intelligent machines, especially intelligent computer programs”.

1  
Overview

1.1   
What is AI?

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Artificial Intelligence is a way of
making a computer, a computer-controlled robot, or a software think
intelligently, in the similar manner the intelligent humans think.

John McCarthy is called the Father of
Artificial Intelligence and as per him Artificial Intelligence is

“The science and engineering of making
intelligent machines, especially intelligent computer programs”.

1.2   
History of AI

The History of AI began in
4th century B.C. whenAristotleinventedsyllogistic logic, the first formal deductive reasoning system.
Later in 13th centuryTalking
Headswere said to have been
created byRoger BaconandAlbertin the same periodRamon Lullinvented machines for discoveringnon-mathematicaltruths throughcombinatoricsand in 1206 A.D. an Arab inventorAl-Jazaridesigned what is believed to be the first
programmable humanoid robot, a boat carrying four mechanical musicians powered
by water flow.

15th and 16th Century

·        
In 1456 Gutenberg Bible was
printed by Johannes Gutenberg using moveable type

·        
Clocks, the first modern
measuring machines, were produced using lathes

·        
Clockmakers extended their
craft to creating mechanical animals and other novelties. For example, see
DaVinci’s walking lion (1515)

17th and 18th Century

·        
Pascal created the first
mechanical digital calculating machine

·        
In between 1662-1666
Arithmetical Machines devised by Sir Samuel Morland were introduced

·        
In 18th Century
large quantity of Mechanical toys like mechanical duck of Vaucanson and von
Kempelen’s phony mechanical chess player were introduced

19 Century

·        
The first programmable machine
with instruction on punched cards was introduced by Joseph – Marie Jacquard

·        
The story of Frankenstein’s
monster was published by Mary Shelley and were made available by project
Gutenberg

20th Century

In 20th Century AI took modern shape and automated
further to a new form.

·        
In 1950’s Early AI programs
like Samuel’s checkers program, Newell & Simon’s Logic Theorist,
Gelernter’s Geometry Engine were introduced

·        
In 1956 AI was adopted at the
workshop held at Dartmouth college which was attended by Allen Newell, Herbert
Simon, John McCarthy, Marvin Minsky and Arthur Samuel became the founders and
leaders of AI research.

·        
In 1958 John McCarthy (MIT)
invented the Lisp language.

·        
In 1962 First industrial robot
company, Unimation was founded.

·        
In 1967 first Dendral Program
by Edward Feigenbaum, Joshua Lederberg, Bruce Buchanan, Georgia Sutherland at
Stanford was demonstrated to interpret mass spectra on organic chemical
compounds. First successful knowledge-based program for scientific reasoning.

·        
In 1980’s LISP machines were
developed and marketed

·        
In 1990’s there were Major
advances in all areas of AI, with significant demonstrations in machine
learning, intelligent tutoring, case-based reasoning, multi-agent planning,
scheduling, uncertain reasoning, data mining, natural language understanding and
translation, vision, virtual reality, games, and other topics.

·        
In 2000’s Interactive robot
pets (a.k.a. “smart toys”) become commercially available, realizing
the vision of the 18th cen. novelty toy makers.

1.3   
Goals of AI

·        
Intelligent execution of user requests
in the operating system

·        
To provide reliability and
better support to customers

·        
To Create systems that
understand, think, learn, and behave like humans for the purpose of learning,
behavior etc.

1.4   
What Contributes to AI?

Artificial intelligence is a science and
technology based on disciplines such as Computer Science, Biology, Psychology,
Linguistics, Mathematics, and Engineering. A major thrust of AI is in the
development of computer functions associated with human intelligence, such as
reasoning, learning, and problem solving.

Out of the following areas, one or
multiple areas can contribute to build an intelligent system.

·        
Philosophy

·        
Computer Science

·        
Psychology

·        
Sociology

·        
Neuron Science

·        
Math’s

·        
Biology

1.5   
What is AI Technique?

AI Technique is a manner to organize and
use the knowledge efficiently in such a way that:

·        
It should be perceivable by the
people who provide it.

·        
It should be easily modifiable
to correct errors.

·        
It should be useful in many
situations though it is incomplete or inaccurate.

According to the area of research,different
types of techniques are used. Some of the examples are:

Intelligent Data Analysis in Medicine

·        
Multilayer perceptrons as
nonlinear classifiers and estimators

·        
Gaussian mixture models

·        
Hidden Markov models

·        
Kernel methods

·        
Bayesian networks

·        
Netalg: Neural Network tool box
for R

Cognitive Modelling

·        
Connectionist models (neural
networks)

·        
Pulsed neural networks

·        
Neuronal modelling based on
differential equations

Knowledge-Based Systems

·        
Temporal data abstraction

·        
Intelligent information visualization,
metaphor graphics

·        
Integration of information
technology with telecommunication

1.6   
Applications of AI

Artificial Intelligence has many
application’s in today’s society and plays an important role in our day to day
life in the fields such as Marketing, Finance, Medical, gaming and many other.
AI has been dominant in various fields as below:

·        
Gaming

AI plays an important role in games such
as chess, poker as it can think of large number of possible moves then human
mind.

·        
Natural Language Processing

Natural language processing makes it
possible to interact with computer that understands natural language spoken by
humans.

·        
Expert Systems

There are some applications which integrate
machines and software to provide explanation and advice to the users.

·        
Vision Systems

These systems understand, interpret, and
comprehend visual input on the computer.

·        
Speech Recognition

These systems are capable of hearing and
comprehending the language in term of sentences and their meanings while human
talks to it.

·        
Handwriting Recognition

This system reads the text written on
paper or on a screen. It can recognize the shapes of the letters and convert it
into editable text.

·        
Intelligent Robots

Robots have the sensors to detect physical
data from temperature, movement, sound, light, heat etc. and perform the task
given by human.

1.7   
Programming with and without
AI?

A typical program has three major segments
input, processing and output. The comparison between regular programming and AI
programming is described in the below table:

Table 1: Programming with and
without AI

Segment

Regular Programming

AI Programming

Input

In regular programming, input is
a sequence of alphanumeric symbols presented and stored as per some given set
of previously stipulated rules and that uses a limited set of communication
media such as keyboard, mouse, disc, etc.

In Artificial Intelligence
programming, the input may be a sight, sound, touch, smell or taste. Sight
means one dimensional symbol such as typed text, two dimensional objects or
three dimensional scenes. Sound input includes spoken language, music, noise
made by objects. Touch includes temperature, smoothness, resistance to
pressure. Smell input includes odors emanating from animate and inanimate
objects. And taste input includes sweet, sour, salty, bitter foodstuffs and
chemicals.

Processing

In regular programming,
processing means manipulation of the stored symbols by a set of previously
defined algorithms.

In AI programming, processing
includes knowledge representation and pattern matching, search, logic,
problem solving and learning.

Output

In regular programming, output
is a sequence of alphanumeric symbols, may be in a given set of colors, that
represents the result of the processing and that is placed on such a medium
as a CRT screen, paper, or magnetic disk.

In AI programming, output can be
in the form of printed language and synthesized speech, manipulation of
physical objects or locomotion i.e., movement in space.

2  
Intelligent Systems

An intelligent system is a machine with
an embedded, Internet-connected computer that has the capacity to gather and
analyze data and communicate with other systems.

2.1   
What is Intelligence?

The ability of a system intelligence is to
calculate, reason, perceive relationships and analogies, learn fromexperience,
store and retrieve information from memory, solve problems, comprehendcomplex
ideas, use natural language fluently, classify, generalize, and adapt new
situations.

2.2   
Types of Intelligence

The types of Intelligence are:

·        
Linguistic Intelligence

·        
Musical Intelligence

·        
Logical – Mathematical
Intelligence

·        
Spatial Intelligence

·        
Intra Personal Intelligence

·        
Interpersonal Intelligence

2.3   
What is intelligence composed
of?

·        
Reasoning

·        
Learning

·        
Problem Solving

·        
Perception

·        
Linguistic Intelligence

2.4   
Difference between human and
machine intelligence?

Table 2: Difference between human
and machine intelligence

Human Intelligence

Machine Intelligence

Humans perceive by patterns

Machines perceive by set of
rules and data

Humans store and recall
information by patterns

Machines search by algorithms

Humans can figure out the
complete object even if something is missing

Machines cannot figure out

2.5   
Intelligence in our day to day
life

Machine intelligence is used in our day
to day life in various areas such as

·        
Post Office

Automatic address recognition and sorting
of mail

·        
Banks

Automatic check readers, signature
verification systems and automated loan application classification

·        
Telephone Companies

Automatic voice recognition for directory inquiries

·        
Credit Card Companies

Automated fraud detection

·        
Computer Companies

Automated diagnosis for help-desk
applications

3  
Research areas of AI

The research area of AI is vast and huge.
Some of the common research areas in the domain of AI are:

·        
Expert Systems

·        
Neural Networks

·        
Robotics

·        
Fuzzy Logic

·        
Natural Language Processing

3.1   
Real life applications of
research areas

There are large number of applications
where AI is helping people in their day to day lives:

Expert Systems

An expert system is used for solving
complex problems by reasoning about knowledge, represented primarily by if-then
rules rather than by conventional procedural code.

Example: Flight tracking systems,
Clinical systems.

Neural Networks

Neural networks are system of
interconnected which exchange messages between each other and are used for
approximate functions or it estimates a large number of inputs which are
generally unknown.

Example: Pattern recognition systems such
as face recognition, character recognition, handwriting recognition.

Robotics

Robotics is mainly composed of electrical
engineering, mechanical engineering and computer science engineering for
construction, designing and application of robots.

Example: Industrial robots for moving,
spraying, painting, precision checking, drilling, cleaning, coating, carving
etc.

Fuzzy Logic

Fuzzy Logic was introduced in 1965. It is
a form of many valued logics in which truth table values of variables may be a real
number between 0 and 1.

Example: Consumer Electronics,
Automobiles etc.

Natural Language Processing

It is a method of communicating with an
intelligent system by using natural language such as English. The input and
output of NLP system is written in text or speech.

Example: Google now feature.

3.2   
Task Classification of AI

The task classification of AI is into 3
classes:

1.    
Expert Tasks

2.    
Mundane Tasks

3.    
Formal Tasks

Expert Tasks

Expert tasks are as follows:

·        
Financial Analysis

·        
Medical Diagnosis

·        
Scientific Analysis

·        
Engineering

o   
Design

o   
Fault Finding

o   
Manufacturing

Mundane Tasks

Mundane tasks are as follows:

·        
Perception

·        
Vision

·        
Speech

·        
Common Sense Reasoning

·        
Robot Control

Formal Tasks

Formal tasks are as follows:

·        
Games

·        
Mathematics

·        
Proving Properties of programs
e.g. correctness.

4  
AI Issues

Since AI is developing at a high pace and
there are different opinions among researchers and developers that it might get
difficult for humans to control. Some of the issues and threats are:

·        
Threat to privacy

·        
Threat to Human Dignity

·        
Threat to Safety

·        
Weaponization

·        
Unemployment

·        
Inequality

·        
Humanity

·        
Racist Robots

5  
Terminology and Abbreviations

Table 3: Terminology and
Abbreviations

Term

Meaning

AI

Artificial Intelligence

NLP

Natural Language Processing

AI

An artificial intelligence is a
machine that can think the way people think.

Machine Learning

Machine learning is a subset of
the larger artificial intelligence category.

Cognitive Computing

It means the same as artificial
intelligence

Neural Network

A computer system inspired by
living brains.

Algorithm

A process or set of rules to be
followed in calculations or other problem-solving operations, especially by
a computer.

Data Mining

It is all about looking for
patterns in a set of data. It identifies correlations and trends that might
otherwise go unnoticed.

Natural Language Processing

It is an area of artificial
intelligence related to understanding and generating speech the way humans
usually use it.

Turing Test

The Turing Test is named for
its inventor, Alan Turing, an early computer scientist who theorized
extensively about artificial intelligence.