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ARTIFICIAL INTELLIGENCE
PRESENTED BY,
BIKAS CHANDRA SADASHIV
Contents
Introduction
History of Artificial Intelligence
Why AI
Limitations of Human Mind
How Does AI Works??
Goals or Field
Applications
Artificial Intelligence VS Conventional Computing
Advantages
Disadvantages
Future
Conclusion
Introduction
Intelligence: “ability to learn, understand and
think” (Oxford dictionary),
‘AI’ is how to make computers do things like
human,
It is a branch of Science which deals with helping
machines finds solutions to complex problems in a
more human-like fashion,
Involves borrowing characteristics from human
intelligence, and applying them as algorithms in a
computer friendly way.
ARTIFICIAL INTELLIGENCE
INCLUDES
 People
 Procedures
 Hardware, software and data knowledge needed to develop computer systems and machines
that demonstrate characteristics of intelligence.
Brief History of A I
 Earliest work in the field of artificial intelligence was done in the
mid 20th century.
 The English Alan Turing may have been the first
 He describes a computing machine that consists of limitless
memory
 1941: First electronic computer (technology finally available )
Brief History of A I
 1956 John McCarthy coined the term artificial intelligence.
 He defines it as “the science and engineering of making intelligent machines”
 He also invented the Lisp Language
 1960s: Checkers-playing program that was able to play games with opponents
 1980s: Quality Control Systems
 2000: First sophisticated walking robot
WHY A I?
Computers are fundamentally well suited to
performing mechanical computations, using
fixed programmed rules. This allows artificial
machines to perform simple monotonous
tasks efficiently and reliably, which humans
are ill-suited to. `
LIMITATIONS OF HUMAN MIND
 Object recognition. People cannot properly explain
how they recognize objects.
 Face recognition. Cannot be passed on to another
person by explanation.
 Naming of colours. Based on learning, not on
absolute standards.
How Does AI Works??
Artificial intelligence works with the help of
Artificial Neurons (Artificial Neural Network) And
• Scientific theorems(If-Then Statements, Logics)
What is Neural Networking??
Artificial neural networks are composed of interconnecting
artificial neurons (programming constructs that mimic the
properties of biological neurons).
Dendrites: Accepts Inputs
Soma: Processes the Inputs
Axon: Turns the processed inputs into outputs
Synapses: The electrochemical contact between neurons
Goals or fields of AI
 Deduction, reasoning, problem solving.
 Knowledge representation.
 Planning.
 Learning.
 Natural language processing.
 Motion and manipulation.
 Perception.
 Social intelligence.
 Creativity.
 General intelligence.
APPLICATIONS OF A I
 Expert systems.
 Natural Language Processing (NLP).
 Speech recognition.
 Computer vision.
 Robotics.
EXPERT SYSTEMS
 An Expert System is a computer program designed to
act as an expert in a particular domain (area of expertise)
Phases in Expert System
 Expert systems currently are designed to assist experts, not to
replace them, They have been used in medical diagnosis, chemical
analysis, geological explorations etc.
Applications of Expert Systems
 Used by geologists to identify sites for drilling or mining
 PUFF:Medical system for diagnosis of respiratory conditions
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.
ROBOTICS
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
Artificial Intelligence VS Conventional Computing
AI software uses the techniques of search
and pattern matching
Programmers design AI software to give
the computer only the problem, not the
steps necessary to solve it
Conventional computer software follow a
logical series of steps to reach a conclusion
Computer programmers originally
designed software that accomplished tasks
by completing algorithms
Advantages
 Ability to simulate human behavior and cognitive processes
Capture and preserve human expertise Fast Response.
 They will probably be increasingly used in the field of
medicine.
 The ability to comprehend large amounts of data quickly.
 A knowledge based expert system, which can cross-reference
symptoms and diseases will greatly improve the accuracy of
diagnostics.
 Object recognition will also be a great aid to doctors.
 Along with images from cats cans or X-ray machines, they
will be able to get preliminary analysis of those images.
Disadvantages
• .
 Self-modifying, when combined with self-
replicating, can lead to dangerous,
unexpected results, such as a new and
frequently mutating computer virus.
 No “common sense”.
 Cannot readily deal with “mixed”
knowledge.
 May have high development costs.
 Raise legal and ethical concerns
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.
Future (-)
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.
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.

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artificial intelligence

  • 2. Contents Introduction History of Artificial Intelligence Why AI Limitations of Human Mind How Does AI Works?? Goals or Field Applications Artificial Intelligence VS Conventional Computing Advantages Disadvantages Future Conclusion
  • 3. Introduction Intelligence: “ability to learn, understand and think” (Oxford dictionary), ‘AI’ is how to make computers do things like human, It is a branch of Science which deals with helping machines finds solutions to complex problems in a more human-like fashion, Involves borrowing characteristics from human intelligence, and applying them as algorithms in a computer friendly way.
  • 4. ARTIFICIAL INTELLIGENCE INCLUDES  People  Procedures  Hardware, software and data knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence.
  • 5. Brief History of A I  Earliest work in the field of artificial intelligence was done in the mid 20th century.  The English Alan Turing may have been the first  He describes a computing machine that consists of limitless memory  1941: First electronic computer (technology finally available )
  • 6. Brief History of A I  1956 John McCarthy coined the term artificial intelligence.  He defines it as “the science and engineering of making intelligent machines”  He also invented the Lisp Language  1960s: Checkers-playing program that was able to play games with opponents  1980s: Quality Control Systems  2000: First sophisticated walking robot
  • 7. WHY A I? Computers are fundamentally well suited to performing mechanical computations, using fixed programmed rules. This allows artificial machines to perform simple monotonous tasks efficiently and reliably, which humans are ill-suited to. `
  • 8. LIMITATIONS OF HUMAN MIND  Object recognition. People cannot properly explain how they recognize objects.  Face recognition. Cannot be passed on to another person by explanation.  Naming of colours. Based on learning, not on absolute standards.
  • 9. How Does AI Works?? Artificial intelligence works with the help of Artificial Neurons (Artificial Neural Network) And • Scientific theorems(If-Then Statements, Logics)
  • 10. What is Neural Networking?? Artificial neural networks are composed of interconnecting artificial neurons (programming constructs that mimic the properties of biological neurons).
  • 11. Dendrites: Accepts Inputs Soma: Processes the Inputs Axon: Turns the processed inputs into outputs Synapses: The electrochemical contact between neurons
  • 12.
  • 13. Goals or fields of AI  Deduction, reasoning, problem solving.  Knowledge representation.  Planning.  Learning.  Natural language processing.  Motion and manipulation.  Perception.  Social intelligence.  Creativity.  General intelligence.
  • 14. APPLICATIONS OF A I  Expert systems.  Natural Language Processing (NLP).  Speech recognition.  Computer vision.  Robotics.
  • 15. EXPERT SYSTEMS  An Expert System is a computer program designed to act as an expert in a particular domain (area of expertise) Phases in Expert System  Expert systems currently are designed to assist experts, not to replace them, They have been used in medical diagnosis, chemical analysis, geological explorations etc. Applications of Expert Systems  Used by geologists to identify sites for drilling or mining  PUFF:Medical system for diagnosis of respiratory conditions
  • 16. 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.
  • 17. 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.
  • 18. 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.
  • 19. ROBOTICS 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
  • 20. Artificial Intelligence VS Conventional Computing AI software uses the techniques of search and pattern matching Programmers design AI software to give the computer only the problem, not the steps necessary to solve it Conventional computer software follow a logical series of steps to reach a conclusion Computer programmers originally designed software that accomplished tasks by completing algorithms
  • 21.
  • 22. Advantages  Ability to simulate human behavior and cognitive processes Capture and preserve human expertise Fast Response.  They will probably be increasingly used in the field of medicine.  The ability to comprehend large amounts of data quickly.  A knowledge based expert system, which can cross-reference symptoms and diseases will greatly improve the accuracy of diagnostics.  Object recognition will also be a great aid to doctors.  Along with images from cats cans or X-ray machines, they will be able to get preliminary analysis of those images.
  • 23. Disadvantages • .  Self-modifying, when combined with self- replicating, can lead to dangerous, unexpected results, such as a new and frequently mutating computer virus.  No “common sense”.  Cannot readily deal with “mixed” knowledge.  May have high development costs.  Raise legal and ethical concerns
  • 24. 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.
  • 25. Future (-) 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.
  • 26. 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.