1) Artificial intelligence (AI) is the study of intelligent machines that can perform functions like human thought. AI research dates back to ancient times but expanded in the 20th century with advances in computing. 2) Early milestones included simulating human thinking on computers in 1956 and the first AI conference that year, which inspired research emulating human reasoning, language, communication and more. 3) AI has many applications today including financial services, healthcare, transportation and more, but still faces limitations, especially in areas like natural language understanding. Fully realizing human-level AI may take decades more of research focused on language, environmental interaction and other challenges.

1. INTRODUCTION TO
ARTIFICIAL
INTELLIGENCE (A.I)
BY :
DR. YASIN ASADI , MOHSEN TAHERI

2. INTRODUCTION
• the study of intelligent machines capable of the same
kinds of functions like human thought.
 AI dates from ancient times but 20th century brought AI
into the possibility.
AI reaches in other fields such areas as information processing,
computer gaming, national security, electronic commerce, and
diagnostic systems.

3. DEVELOPMENT OF ARTIFICIAL
INTELLIGENCE
• In 1956 Herbert Simon and Allan Newell at University of
Pennsylvania :
• simulated human thinking on computers.
• The first AI conference at Dartmouth College in 1956.
• This conference inspired researchers to take on projects
that emulated human behavior in the areas of :

4. • of reasoning
• language comprehension
• and communications
• AI has taken two major directions:
• 1. psychological
• 2. physiological
• Some AI developers interested in :

5. • Modern field of interest is expert systems.
 Learning more about the human brain to
mimic it’s mechanism .
 Others are more interested in making
computers perform a specific task involve
the capabilities of the human brain.

6. • search for AI goes beyond …
• neuroscience,
• linguistics,
• cybernetics, I
• information theory,
• mechanical engineering,
• and a lot of branches.

7. MORE INFORMATION USES AND
CHALLENGES OF AI
• AI programs have a broad array of applications :
• financial institutions,
• scientists, psychologists,
• medical practitioners,
• design engineers,
• planning authorities,
• and security services,
• AI techniques are used to browse the Internet.

8. USAGE OF AI PROGRAMS
• AI programs highly uses for:
• play games,
• predict stock values
• , interpret photographs,

9. • diagnose diseases,
• plan travel schedule,
• translate languages,
• take dictation,
• teach logic, compose music,
• and learn to do tasks better

10. KASPAROV VS. DEEP BLUE
• A supercomputer called Deep Blue beat world
chess champion Garry Kasparov in 1997.

11. MIMIC HUMAN BEHAVIORS
• They can even mimic human behaviors
• AI can compose masterpiece just like a famous
composer
• WABOT-2 and Inventor

12. DESPITE CONSIDERABLE SUCCES
SES
•AI programs still have many limitations.
•Especially in language and speech recognition.
•Translations are imperfect.
•Dictation is reliable if only…

13. DEVELOPING NATURAL
LANGUAGE
• An important focus of AI involves natural
language
• Understanding
• Recognition
• Then Answer specific Question

14. AI & ROBOTS
•important branch of AI is development of
robots
•Interact with environment was an example
•WABOT-2 is an example.
•For using in hospitals.
•Helping disabled people.

15. AI & NASA
•Scientists with the (NASA) developing robust AI programs
•For next generation of Mars rovers

16. MODELING
• AI systems need to model :
• the richness of human memory
• Understanding this is the Question

17. TYPES OF AI
• AI primarily focused on two areas:
• Developing logic-based systems
• Using Awareness and biological
• In general, categorized within three types :
• Symbolic,
• Connectionist,
• Evolutionary.

18. SYMBOLIC AI
• Symbolic AI is based in logic.
• uses sequences to tell the computer what to do next.
• IF-THEN rules.
• Illogical AI are not used for problem-solving.
• For modeling how humans think.
• But they are inflexible

19. CONNECTIONIST AI

20. CONNECTIONIST AI
• Consequently:
• Connectionist is more flexible than symbolic
AI.
• Connectionism is weak at doing logic.
• What symbolic AI does well, connectionism does
badly, and the opposite.
• Hybrid systems combine the two, switching
between them as appropriate.

21. EVOLUTIONARY AI
• Evolutionary AI draws on biology.
• Make random changes in their own rules.
• Often used in modeling artificial life (A-Life)
• Technological examples algorithms used for
computer animation.

22. PHILOSOPHICAL DEBATES OVER
AI
• People often ask:
• if artificial intelligence is possible, but the
question is dim.
• computers could never do are now possible
due to AI research .

23. PHILOSOPHICAL DEBATES OVER
AI
• The larger question of whether any program or
robot could really be intelligent, no matter how
humanlike its performance.
• involves highly debatable issues in the
philosophy of mind.

24. PHILOSOPHERS & AI RESEARCHERS
SAYING:
• intelligence can arise only in bodily creatures
sensing and acting in the real world.
• If so, Robots are truly intelligent artifacts.
• If not, then a mere AI program might be
intelligent.

25. ALAN TURING
• British mathematician ,
• logician and computer scientist
• Alan Turing proposed
• what is now called
• the Turing Test.

26. TURING TEST

28. A DIFFERENT VIEW
• American philosopher John Searle has expressed a
different view.
• Programmed robot might behave exactly like a
human.
• It cannot understand anything it says.
• Brains can ascribe meaning to symbols .
• Whereas metal and silicon cannot.

29. THE MORAL QUESTION IS
•If an AI system were conscious, it
would arguably be wrong to “kill”
it, or even to use it as a “slave.”

30. FUZZY LOGIC
• a form of logic used in some expert systems and other artificial-
intelligence programs
• It’s originated In 1965 by
• Lotfi Zadeh,
• University of California Berkeley
• In aristotle logic range of values
• between 1 (true) and 0 (false).

31. FUZZY LOGIC
• probability rather than as a certainty.
• Answers:
• Probably true,
• Possibly true,
• Possibly false,
• Probably false.

32. THE FUTURE OF ARTIFICIAL
INTELLIGENCE
•Building intelligent systems remains a frightening
task, and one that may take decades to fully
realize.
•AI research is currently focused on:
•Natural language
•Respond to their environment
•Nearly all industrial, governmental, and consumer
applications are likely to need AI capabilities in the
future.

33. REFRENCE
•
• Professor of Philosophy and Director of the Turing
Archive for the History of Computing, University of
Canterbury, Christchurch, New Zealand. Author of
Artificial Intelligence.
•
• Encyclopædia Britannica 2012.