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 INTRODUCTION
 EARLY HISTORY
 AI in 21st century
 CHALLENGES
 APPROACHES
 PROS & CONS
 APPLICATIONS
 ARTIFICIAL INTELLIGENCE VS
HUMAN INTELLIGENCE
 FUTURE OF AI
 PROGRAMMING LANGUAGES USED IN AI
-STANDS FOR ARTIFICIAL INTELLIGENCE.
{ AI is the study of computer system that
attempt to model and apply the intelligence of
the human mind in machines}
TYPES OF ARTIFICIAL INTELLIGENCE:-
 weak AI
 Strong AI
 Also known as Narrow AI
 Can react to only limited things
 Bounded by some rules
 Examples-characters in video games, apple
siri, cortana and etc.
 Also known as True intelligence or Artificial
General Intelligence(AGI)
 Smarter enough to mimic the human brain
 Artificial human
 Examples-movies(terminator , iron man)
 In 1950 English
mathematician Alan Turing
wrote a landmark paper
titled “Computing Machinery
and Intelligence” that asked
the question: “Can machines
think?”
 Further work came out of a
1956 workshop at
Dartmouth sponsored by
John McCarthy. In the
proposal for that workshop,
he coined the phrase a
“study of Artificial
Intelligence”
 Lack of compute power
 Investment
 Tolerance power
 Intuitive thinking's
 Judging power
 Thinking humanely
 Thinking rationally
 Acting humanely
 Acting rationally
Pros:-
 Less room for error
 Always complete the given task in given time
 Work in harsh situation
 Can work continuously
 Decision making
 Reliable and easy to use for everyone
 Not affected physically or mentally
Cons:-
 Expensive to implement
 Dependency on machine
 Reduce employment
 Restricted work
 Decision making
 Lack of improvement
 Lack of creativity
 Large consumption of energy
 Finance(Banks)
 Games
 Speech recognition
 Facial Recognition
 Medical Diagnosis
 Transportation(self-driving car)
 Cyber security
 Several industries
 Management
HUMAN INTELLIGENCE ARTIFICIAL INTELLIGENCE
Can learn several skills Designed for limited tasks
Better decision with experience Cant even compete in mobility with
6 year old kid
Learn with mistakes Time need to teach system is very
high
biased Less biased
Speed of execution is less Very speed execution rate with
compare to HI
Accuracy is less Accuracy is high
Less durable Highly durable
 Self driving cars
 Humans personal assistant
 AI organs
 Medical treatment
 Soldiers
 Artificial mind which is stronger then human
 Java
 Python
 Lisp
 Prolog
 AIML(artificial intelligence markup language)
 Haskell
 Matlab
 Perl
 Julia
Ai

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Ai

  • 1.
  • 2.  INTRODUCTION  EARLY HISTORY  AI in 21st century  CHALLENGES  APPROACHES  PROS & CONS  APPLICATIONS  ARTIFICIAL INTELLIGENCE VS HUMAN INTELLIGENCE  FUTURE OF AI  PROGRAMMING LANGUAGES USED IN AI
  • 3. -STANDS FOR ARTIFICIAL INTELLIGENCE. { AI is the study of computer system that attempt to model and apply the intelligence of the human mind in machines} TYPES OF ARTIFICIAL INTELLIGENCE:-  weak AI  Strong AI
  • 4.  Also known as Narrow AI  Can react to only limited things  Bounded by some rules  Examples-characters in video games, apple siri, cortana and etc.  Also known as True intelligence or Artificial General Intelligence(AGI)  Smarter enough to mimic the human brain  Artificial human  Examples-movies(terminator , iron man)
  • 5.  In 1950 English mathematician Alan Turing wrote a landmark paper titled “Computing Machinery and Intelligence” that asked the question: “Can machines think?”  Further work came out of a 1956 workshop at Dartmouth sponsored by John McCarthy. In the proposal for that workshop, he coined the phrase a “study of Artificial Intelligence”
  • 6.
  • 7.  Lack of compute power  Investment  Tolerance power  Intuitive thinking's  Judging power
  • 8.  Thinking humanely  Thinking rationally  Acting humanely  Acting rationally
  • 9. Pros:-  Less room for error  Always complete the given task in given time  Work in harsh situation  Can work continuously  Decision making  Reliable and easy to use for everyone  Not affected physically or mentally
  • 10. Cons:-  Expensive to implement  Dependency on machine  Reduce employment  Restricted work  Decision making  Lack of improvement  Lack of creativity  Large consumption of energy
  • 11.  Finance(Banks)  Games  Speech recognition  Facial Recognition  Medical Diagnosis  Transportation(self-driving car)  Cyber security  Several industries  Management
  • 12. HUMAN INTELLIGENCE ARTIFICIAL INTELLIGENCE Can learn several skills Designed for limited tasks Better decision with experience Cant even compete in mobility with 6 year old kid Learn with mistakes Time need to teach system is very high biased Less biased Speed of execution is less Very speed execution rate with compare to HI Accuracy is less Accuracy is high Less durable Highly durable
  • 13.  Self driving cars  Humans personal assistant  AI organs  Medical treatment  Soldiers  Artificial mind which is stronger then human
  • 14.  Java  Python  Lisp  Prolog  AIML(artificial intelligence markup language)  Haskell  Matlab  Perl  Julia