Artificial intelligence

CONTENTS
INTRODUCTION TO A.I.
EVOLUTION OF A.I.
BRANCHES OF A.I.
APPLICATIONS OF A.I.
CONCLUSIONS ON A.I.

Claiming to be able to recreate the capabilities of the
human mind, is both a challenge and an inspiration
for philosophy.
• It is the science and engineering of making
intelligent machines, especially intelligent
computer programs.

TURING TEST
* Intelligence is defined as the ability to achieve human level
performance in all cognitive tests, sufficient to fool a human
interrogator.
* 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.
* Proposed by Alan Turing(1950), a British Computer
Scientist.

DEFINITIONS
* A.I is a branch of computer sciences dealing
with symbolic, Nonalgorithic-Methods of
problem solving.
* AI works with pattern matching methods which attempt to
describe objects , events or processes in terms of their
qualitative features and logical and computational
Relationship.

What is Intelligence ?
 To respond to situations very flexibly.
 To make sense out of ambiguous or contradictory messages.
 Torecognize relativeimportanceofdifferentelementsof situations
 To find similarities between situations despite difference
 To draw distinctions between situations despite similarities which may link them.

1943 – McCulloh and Pitts, Boolean circuit model of brain.
1950 – Turing’s computing machine and intelligence.
1950’s – Early AI programs including Samuel’s checker program, Newell and
Simon’s logic theorist, Gelisnters geometry engine
1956 – Dartmouth conference.
HISTORY

HISTORY
1952-69 – “Look, Ma, no hands!” era.
1958 – McCarthy moves to MIT, LISP was born.
1965 – Robinson’s complete algorithm for logical reasoning.
1966-74 – AI discovers computational complex.
1969-79 - Early development in knowledge based systems.

1980-88 : Expert system industry booms.
1988-93 : Expert system industry busts.
1985-88 : Neural networks return to popularity.
1995 : Agents… Agents… Agents.
(present)
HISTORY

Can AI System
Work as Efficient
as
Human Brain..?

 How complicated is our brain?
 Neuron
 10 12 neurons in a human brain
 many more synapses (10 14) connecting these
neurons
 cycle time: 10 -3 seconds (1 millisecond)
 How complex can we make
computers?
 108 or more transistors per CPU
 supercomputer: hundreds of CPUs, 1012 bits of RAM
 cycle times: order of 10 - 9 seconds
 Conclusion
YES
 Less interconnections (wires or synapses)
 Faster

Representation
Facts about the world have to be represented in some way.
Usually languages of mathematical logic are used.
Common Sense, Knowledge and Reasoning
This is an era in which AI is farthest from human level. While
there has been considerable progress, e.g. in development systems of non
monotonic reasoning and theories of action

APPLICATIONS OF A.I.
 Expert systems.
 Natural Language Processing (NLP).
 Speech recognition.
 Computer vision.
 Robotics.
 Automatic Programming.

An Expert System is a computer program designed to act as an expert in a
particular domain (area of expertise).
Expert systems currently are designed to assist experts, not to replace them,
They have been used in medical diagnosis, chemical analysis, geological
explorations etc.
Domain of E.S.
Knowledge base
Facts Heuristics
Phases in Expert System
EXPERT SYSTEMS

Natural Language
Processing
The goal of NLP is to enable people and computers to communicate in a
natural (humanly) language(such as, English) rather than in a computer
language.
The field of NLP is divided in 2 categories—
 Natural Language understanding.
 Natural Language generation.

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.

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 A.I
helps computer to understand what they see
through attached cameras.

A Robot is a electro-mechanical 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.

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.
(+)

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.
FUTURE (-)

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.

Artificial intelligence

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Artificial intelligence